{
 "cells": [
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "# 性能分析",
   "id": "c28f28e349519fea"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-06-12T13:15:49.246349Z",
     "start_time": "2025-06-12T13:15:49.037351Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# 设置中文显示\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.rcParams['axes.unicode_minus'] = False\n",
    "\n",
    "# 创建数据集\n",
    "metrics = ['Accuracy', 'Precision', 'Recall', 'F1-score']\n",
    "models = ['Perceptron', 'Logistic', 'MLP', 'CNN', 'SVM']  # 添加SVM\n",
    "\n",
    "data = np.array([\n",
    "    [0.8811, 0.8810, 0.8811, 0.8808],    # Perceptron\n",
    "    [0.9157, 0.9155, 0.9157, 0.9155],    # Logistic\n",
    "    [0.9740, 0.9741, 0.9740, 0.9740],    # MLP\n",
    "    [0.9897, 0.9897, 0.9897, 0.9897],    # CNN\n",
    "    [0.9810, 0.9809, 0.9809, 0.9809]     # SVM（新增数据）\n",
    "])\n",
    "\n",
    "# 创建DataFrame\n",
    "df = pd.DataFrame(data, index=models, columns=metrics)\n",
    "\n",
    "# 绘制热度图\n",
    "plt.figure(figsize=(12, 7))  # 增大画布尺寸\n",
    "ax = sns.heatmap(df, \n",
    "            annot=True, \n",
    "            fmt=\".4f\", \n",
    "            cmap=\"YlGnBu\", \n",
    "            vmin=0.85, \n",
    "            vmax=1.0,\n",
    "            linewidths=0.5,\n",
    "            cbar_kws={'label': '性能得分', 'shrink': 0.8})\n",
    "\n",
    "ax.set_title('模型性能对比热度图', fontsize=16, pad=20)  # 更新标题\n",
    "plt.xlabel('评估指标', fontsize=12)\n",
    "plt.ylabel('模型类型', fontsize=12)\n",
    "plt.xticks(rotation=45, ha='right')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ],
   "id": "6589e5337a9be53d",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1200x700 with 2 Axes>"
      ],
      "image/png": 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btqzy5cuX5fMAAACegUQJAOC2mj17tiwWi4oUKaI8efLozTff1KBBg7R69Wp7wsLX1zfDH5YmkynNsB2LxaKxY8fqt99+U/PmzXX//ffbj6VWYcTFxdn39erVS7169dLly5d16NAh+6orNy453KJFCxUsWFD33XefQ6JEkipWrKi1a9cqJibGPnlseiuhJCQkKC4uTmazOU0FRGoiYO/evQ5zhaROMpp6/qZNm3T06FF71UxW8uXLpy+++ELPPfecBg8erObNm8tms+mxxx6TJBUrVkyXL1/WlClT1KJFi2y1mVMlSpTI9rkff/yxSpYsqXz58un999/XkSNH0iyrazQaFRcXp3vuuUfz5s3T33//rZ49e0pKTk4EBwdr9uzZatSokcOcMqmJkpuHvcTGxspqtTpU49wodQhOVpKSkrRnzx5t2bJFv//+uzZt2qQSJUpo7Nixuvfee/X+++/r7bfftq/g9NBDD9mXfQYAAJ6LRAkA4LY5e/asvv76azVu3FiRkZG6fPmyWrZsaZ+TonTp0pKkZ599NtN2qlevbv/7Y8eO6fnnn9fFixdVpkwZDR8+3OFcHx8fFS9ePN0hFCdPnlSHDh0kJU8KeuMQiVKlSql9+/YZxmA2mzVjxow086NIaVe9GTVqlJ577jmHfanJkaVLlzpULezbt0/Sv/O1rFy5UgsWLHCo0Dhx4oRmzJihgQMHpjt5q5+fn7744gt16tRJK1asUGBgoH0ITL58+dS7d2+NGTNGX3/9tV555ZUM7/FOKF++vMP2zQmnuLg4DR8+XH5+fvrmm2/066+/avjw4Tp+/Ljy5s2r//u//1OjRo00ZcoU/fnnnw5zpaSuJJQ/f36HNvv06WMflpSeypUrZzv+KVOmaOPGjapSpYreeecd1axZUyNGjFD79u01ffp0HThwQN99951WrVqlP//8U0899VS22wYAAO6JRAkA4LZISEhQ//79FRsbq/79+9uHb6QuEVy4cGElJCQ4DAdZtGiR3nvvPX3//fcOlQI3DqMoU6aMOnbsqK1bt+rDDz9Ms1zswIED9cADD6hHjx4aPHiwwxKtVatW1TPPPKNChQqpU6dOaSZGzUrNmjXVt29f+9COm1e9SUhIUGxsrCpVqpRhG6lLD2cktbrC19dX4eHh+vrrr7VkyRIZDAaVLl1aPXr0SPe6EiVK6KWXXtL7778vLy8vxcXF2YeFdOrUSZ988olmzpyp559/3qGSxhVS5ybZvXu3QyVRYmKiBg0apIMHDyo0NFQBAQFq3769SpUqpbp162r//v1aunSpYmJiFBsbmyaxlTq0xt/fX5GRkVq2bJnMZnOaoTg3+/3331W6dOks558xGo169913FR8fb0+y/frrr7p69apGjhyp8ePHq3nz5ho7dqzeffddnTx5MsNJigEAgOcgUQIAuC3i4+NVsGBBtW3bVhUrVnQ4VrhwYZ07d04Wi0Vms9leYXHu3DlJyVUQqfNH2Gw2Wa1WxcbG2n+c9u3bVzabTXFxcUpISJCXl1eayoRz586lO9/E2LFjFR8ff0vJgvr166t+/fr27eyuenOjjIbepEq9j1atWungwYMKDg7Wm2++qQ4dOiggICDDdq9du6bZs2crf/78OnbsmMaNG6d3331XUnLypV27dpo/f762b9/ucA+34tixYypYsOAtX79q1Sp9+umnkqTnn39eUnI1yFtvvaX169erXbt29lVvpH8n8x04cKAOHTqkVatWqVatWmkmAU4dMhUYGKhLly7pgw8+UN68eXXt2jWZTKZ0lxa+ePGifZWc7Lhx6edjx47p4Ycf1s8//6wNGzZo9uzZSkxMlJeXl7y8vNJUzwAAAM9EogQAcFv4+flp6tSp9hVTbjZ58mQtWbIk3WPpDVcwmUwOw1TCw8OznED0rbfe0ltvvZXusR9++MG+osqdtHnzZocETnh4eLrnPfzwwxo1apRq1qyZ7nwoN5swYYIuXbqkOXPm6LvvvtOCBQv06KOP2pMJXbp00YsvvqiSJUvecuxHjx7VZ599prCwMHuiIzMxMTHpzj3TuXNn+fv76+GHH7Yn0fLkyaO6devKZDLZEzw3K1y4sEJDQ2UymRxWTboxPm9vbxUvXlwlS5bUnj17JEnjx4/XV199pc8++0zVqlWzn5+66k2vXr0c9meHzWZTjx49dObMGdWrV0/NmjXThx9+mGbYDwAA8HwkSgAAt43ZbFbhwoXTPTZ48GANHDhQXl5eMplMOnTokF588UU99dRT2rp1q4KDgzV16lT7ZK43Ts4qJc/58dprr8nb21teXl7y9va2Hzt06JCWLVumVq1aOUz0mpSUJIvFIovFkmbIzp2SuoxxVt55551st7l06VJ9//33evbZZ1WvXj1VqFBBmzdv1vDhw1WjRg0FBASoePHitxqy/vnnH/uSy1arVXXq1FGJEiXsiav0xMfHq3HjxmrQoIHGjh1rHwYkJVdiXLx40SFpc/LkSXXv3l3du3eXwWDQpUuXtHjxYj377LP2VW4+++wzTZ06VQsXLkwzAawkbdmyRZUqVUqTQOnXr5/Wr1+vfv366ZtvvlHJkiW1fft2jRo1So0aNVLfvn0zvf+bJxNO3Td48GD99ttvWr16tX777TeNHj1aDRo00OTJkx3uN1VWSw8DAAD3RKIEAHBH3DiMJDIyUmPGjFFAQIBGjhypP//8U2+88YbGjRunsWPHOiRBUpUvX16DBg1Kt+3Vq1dr2bJlatasmZ588skcx5a6xHDqX2+ntWvXOsyXsWHDhmwlRSwWi15//XX169fPofphzZo1euedd1S1alV7OwEBARo8eLCGDRumSZMmady4cTmO86+//pIkLVmyRF9//bWMRqOaNm2q1157zT657q+//ipJaZJYkrRx40ZdvXpVe/fuTZM0mDZtmrZs2aLHHntMNWvW1I8//qiBAwfqs88+s6/Ws2PHDr3//vuyWq3q1auXJKl9+/b6/PPPNWrUKH3//fcOCZGDBw/q/Pnzat26dZpYfH199fHHH+u5557T888/r969e2v8+PGqUKGCPvrooyyXBE4vUeLl5aWmTZuqadOmGjlypDZs2KAffvhB+fPnTzdJklE7AADA/ZEoAQA4RXpJB5vNptWrV2v8+PGKiYnRrFmzlD9/fjVr1kx9+/bVxx9/rLNnz2rs2LEKDg6+Y7GmLheb+leLxaKTJ0/KbDbL29vb/sM6dZWVqKgoXbhwQVLyhKQWi0UFChRwWKEm9Udy8eLFHeYoyWiuD5vN5jDk5uDBg9q4caOKFStmT5QsWLBAY8aMUWBgoGbMmOFQZdGuXTvt2LHDvqzuzVKTGxkN6zl16pT9vFatWql3794OqwSl3ouUPOxn06ZN9rYSExO1cuVKSckTyd5o06ZN+vPPP9W6dWvVrFlTktSgQQPlyZNHX331lT1R0qRJE5UuXVrz58/XK6+8IrPZrGLFiunVV1/V1KlTtWjRIod5TL7//nt7W+m59957NWTIEA0bNkzvvPOOChQooHHjxmW4LPWNrFarrl27ps8//zzT81ITSDefd+DAAftzAQAAnodECQDAKaxWqz1ZcPjwYS1evFhr165VRESEatSooS+++MLhh3ifPn1kNpv14YcfqkWLFmrVqpVeeeUVxcbGavHixZmuZHLs2DFJyUNSdu3ale45CQkJslgsatq0qR599FGHYxaLxX6OJJ05c0YtWrTI8N7SG7oxcOBAhxVqMqomSE1IpEpNdixbtsxhDpVvvvlGktSsWTNJycmZJUuWqFSpUpo7d26aIU4Gg0GhoaFpvm/OnDk6d+6c1q1bJ0npTnAqSW+88YZOnDihV155RQ888EC65zz11FNavXq1fv/9d82ePdvhWJ48edSuXTuHpZMTExM1btw4eXt7q3///vb9/v7+evLJJ7V06VKdPXtWJUqUkNFoVIcOHfThhx/q559/tleKvPLKK/r66681ZcoUPf3008qbN68uX76s77//XkFBQXr44Yft7V68eFH79+/Xli1btG7dOv3zzz8qWLCg7r//fm3btk0tW7bUfffdp2rVqqlcuXIKCgpSoUKFVKhQId133332dqxWq65evaoPPvgg3eeQXVSUAADgmUiUAACc4vr164qNjZUkFS1aVKtXr5bNZlNoaKjat2+f7vCHHj16qEqVKpowYYL27NmjkiVLav369Vq8eLF8fHwyHTJRsGBB7dixQzt27Ej3eGqiJCgoKMNESepfCxcurIkTJ9qXms3se1PbvXFulNT7v/k7Xn31VW3fvl0VK1ZUmTJlJElPPvmkVqxYoSFDhjicbzAY1KJFCzVp0kRScnJh9uzZio6OztF8K2fPntXs2bNlMBj08MMPpztURZI9SZWZPHnyZGtS11SHDh2SxWJRp06dHFaPkaQnnnhCR48e1ZUrV1SiRAlJ0jPPPKMTJ044rB7j6+urN954QxcvXrTP+REVFaVatWqpVq1aMhgMGjVqlJYvX66YmBhJyf8uNGjQQD179lTTpk1lNpt1+vRprV69Whs3btTq1at15coV+3eMGDEiTaIkMDBQa9euzfa93mjo0KFasmQJFSUAAHgog80ZA7IBALjJxYsXFRAQkOX8EFLyMJTLly9nujyuJ4qPj5fZbM7Wqja3y+nTp3Xw4EFVrVrVJc8zdWLe7Ax5uZW2TSaTLl26pNmzZ6tKlSp64IEHsjVs6/jx4zp48KCOHDmiLl26OAxjOnr0qGw2m+65557bHjMAAHB/JEoAAAAAAABSZP3HegAAAAAAALkEiRIAAAAAAIAUJEoAAAAAAABSkCgBAAAAAABIQaIEAAAAAAAgBYkSAAAAAACAFCRKAAAAAAAAUpAoAQAAAAAASEGiBAAAAAAAIAWJEgAAAAAAgBQkSgAAAAAAAFKQKAEAAAAAAEhBogQAAAAAACAFiRIAAAAAAIAUJEoAAAAAAABSkCgBAAAAAABIQaIEAAAAAAAgBYkSAAAAAACAFCRKAAAAAAAAUpAoAQAAAAAASEGiBAAAAAAAIAWJEgAAAAAAgBQkSgAAAAAAAFKQKAEAAAAAAEhBogQAAAAAACCFl6sDcJa9l1e4OgQg16pSqKX2XaEPAq5UuWBL3oWAC/EuBFyvcsGWrg4BHoqKEgAAAAAAgBQkSgAAAAAAAFKQKAEAAAAAAEhBogQAAAAAACAFiRIAAAAAAIAUJEoAAAAAAABSkCgBAAAAAABIQaIEAAAAAAAgBYkSAAAAAACAFCRKAAAAAAAAUpAoAQAAAAAASEGiBAAAAAAAIAWJEgAAAAAAgBQkSgAAAAAAAFKQKAEAAAAAAEhBogQAAAAAACAFiRIAAAAAAIAUJEoAAAAAAABSkCgBAAAAAABIQaIEAAAAAAAghZerA0i1Y8cOffjhhzpz5oxsNpvDsTVr1rgoKgAAAAAAkJu4TaLkf//7n2rUqKFevXrJ29vb1eEAAAAAAIBcyG0SJVFRUerfv78CAwNdHQoAAAAAAMil3GaOkq5du2ratGlKTEx0dSgAAAAAACCXcpuKkpMnT2rdunVq0qSJHnzwQeXLl89+bNy4cS6MDAAAAAAA5BZukygJDAzU888/7+owAAAAAABALuY2iZI+ffrY/z4yMlIBAQEujAYAAAAAAORGbjNHicVi0bhx41SjRg098sgjqlGjhiZMmCCLxeLq0AAAAAAAQC7hNomSCRMmaOfOnZo5c6Y2bNigmTNnavv27Zo4caKrQwMAAAAAALmE2yRKfvrpJ40fP14PPfSQihQpooceekjjxo3Tjz/+6OrQAAAAAABALuE2iRJ/f38dOXLEYd+RI0fk7+/voogAAAAAAEBu4zaTufbv318DBw5Uq1atFBwcrBMnTigsLEwTJkxwdWgAAAAAACCXcJuKkieffFJz586VJG3dulUGg0Hz58/XE0884eLIAAAAAABAbuE2FSWSVK1aNVWrVs3VYQAAAAAAgFzKbSpKIiIiFBcX5+owAAAAAABALuY2iZKXX35Zu3btcnUYAAAAAAAgF3ObREnbtm21ePFiV4cBAAAAAAByMbdJlNSvX1/Hjh1Tjx49tG7dOm3dutX+AQAAAAAAuBPcZjLXt99+W5J0/vx5jR492r7fYDBozZo1rgoLAAAAAADkIm6TKFm7dq2rQwAAAAAAALmc2wy9AQAAAAAAcDW3SZT89NNPslqtDvu2bdum//3vfy6KCAAAAAAA5DZukygZOHCgYmNjHfYFBwfr559/dlFEAAAAAAAgt3H5HCWnT5+WJNlsNp05c0b58uWzb69bt04lSpRwZXgAAAAAACAXcXmipEmTJjIYDDIYDGrVqpV9v8FgUOnSpfXuu++6MDoAAAAAAJCbuDxREh4eLkmqWLGitm7dqvz587s4IgAAAAAAkFu5zRwl99xzj0wmk6vDAAAAAAAAuZjLK0pSrVy50tUh4D84FnFG00IX6OzJi2rWuq669Gkpg8GQ4fk2m02fT1yk39fsVFKSTXUbPaAegzvIJ493psdShe8+ommhCzRt4dA0bWd2DLibHYs4o2ljFuhMSj98uW/W/XDGxEX6fXVKX3v0AfW8oR9mdCxV+O4j+njMAn3yvWNf+2PNLs2ZGqbERKu6vdlKDZs/5LR7BtwJ70LA9e7kuzCj9118XIKmjP5GOzfvl7fZS489VUtd+raU0eg2f0YNIAtu01utVqvmzp2rLl266Omnn9bLL7+sb775Js2SwXA/CZZEjRs0S/dWDNKk2f114sg5rf1xa6bX/LbyL506fkHvzx2g96b30fEj57R43posj0lSRPgJTRgyRwmWxDTtZnYMuJslWBI1duAslasYpElz+uvkkXNauyIb/fDYBX0wb4DGzuijE4fPadHcNVkek6SIf05o/OA5Skhw7GvHIs5o8siv1fGVZho5pYe+/fwXnTp2/vbfMOBmeBcCrncn34WZve+WfvWrvLxM+njBEL0z+VVt+vXvLOMAPFVkZKSaNGmikydPZuv8LVu2qEWLFqpbt65mz57tcOznn3/WY489pgYNGmjFihXOCDfb3CZR8t577+nrr79WkyZN1KdPHzVu3FizZs3S+PHjXR0asrB90z+6HhOrbv1aq0RQEb3w+lNas/zPTK85tO+46j1WTcVKBqhM+ZKq2+gBnT15MctjcbHxmjB0rlp0bJCmzcyOAXe71H74Sv/WKpnSD1dn0Q8P7j2u+k3+7Wt1Hv23r2V2LLWvPZVOX1u97E9VrVlejz/zsMqUL6kWHR/Rbyv/uv03DLgZ3oWA693Jd2Fm77uD+47r0SdrqnAxf91XubSq1blPZ09ecu7NAy4QGRmpXr166dSpU9k+//XXX9fTTz+tBQsWKCwsTJs3b5YkHThwQIMGDVLv3r01c+ZMTZ06VYcPH3Zm+Jlym0TJjz/+qGnTpqlr165q0aKFunXrpmnTpmnZsmWuDg1ZOHrwtO6vUkY+ecySpLLlS+rk0XOZXhN8Twmt/+UvXbl0TefPRGrj6h2qVuf+LI+ZvEwa93lfVa5+T5o2MzsG3O3S9MP7su6HpcuV0Lqfb+hrq3aoekpfy+yYycukcV/0VeUH0/a1owdPq2qt8vbt+6qUVkR49v6EAfBkvAsB17uT78LM3nely5XQquV/KuZarI4fPqu/fv/Hfh1wNxkwYIBatmyZ7fOXL1+uYsWK6Y033lDZsmXVu3dv/fDDD5Kk77//XnXr1lXHjh1VoUIFvfDCCy7NBbhNoiQwMFDnzzuWZ587d04lSpRwUUTIrusx8SpWKsC+bTAYZDQaFX31eobXNHumruKuW/TK06PUq+17KlYyQI89VSvLY97eXipczD/dNjM7BtztbrkfxlrU7alR6tnmPRUvFaDHnq6V5bHM+lpyHIXt23nz5dHlC1G34xYBt8a7EHC9O/kuzOx9165LEx34+6hebPaO+j03SQ83ruqQVAHcncViUXR0tMPHYrGkOW/MmDHq0qVLttvdv3+/6tata583qFq1atq7d6+k5NVwH374Yfu5Nx5zBbeZzLVs2bLq27evHn/8cZUsWVInT57UmjVr9OSTT2ratGmSpD59+rg4SqTHZDJK3o7/KnmbvRQflyC/Aulfs2LBeuXL76sZS9+RwSBNH/+D5n68Qt36tc70GID0mUxGeZtz2A+/W698fr76fFlyX/ts3A39MJNjmcbhZZS3978rmKXGANzteBcCrncn34WZve++mfGzKla/Rz3+104x12L10chv9OPCDXq6U0On3TtyJ9/Szzml3Yn/q2//DZ6qT58+6tu3r8O+4ODgHLUbHR2te++9177t5+dnL5aIiYlRUFBQusdcwW0qSnx8fPTkk0/KZDLp/PnzMpvNatGihQwGg06dOpXtcU+48/wK5NXVKzEO+2Kvx8vLO+Plnjf8sl3PvNBYRUsUUpHihfRC76e1JuzPLI8BSJ9fgby6ejln/XD9L9vV5sV/+9qLvZ+2j+XO7FiWcdzw/wdxWcQA3C14FwKudyffhZm979b/sl3Pdn9CBQPyK7BMMXXo1kyrl2+53bcLOE3Pnj31119/OXx69uz5n9s1mUwym832bR8fH8XFxWV5zBXcpqJk3Lhxrg4Bt+i+ysFavXyzffvc6UtKTEiUX4G8GV6TlGRT1OVo+/aVS1eVlGTL8hiA9JWvHKxVy3LWD20397XIf/taZscyjaNSsPb/fVTNWteVJB3ef0oBRRkGgLsf70LA9e7kuzCz913yddcklUy+7tI1JSUl3Z6bBG5gMDin7sFsNjskLW4Xf39/RUZG2rdjYmLk7e2d5TFXcJtESUJCgmbOnKm1a9fqzJkzmjVrlkJCQjR58uQcl/Tgzqr8YDldj4nXmhVb1LRlHS2as0bVat0vk8momGuxypPXJ7kk+aZrlsxbK6PRoMREq5bM/1W1G1TO8hiA9FVJ7YdhW9S0VR39MGeNqtXOvB9WerCcFs9N6WsJVi2e/6vqNKyc5bHM1Husmob1+Fgtn22kYqUC9OPCDXr0yZpOuWfAnfAuBFzvTr4LM3vfVXrwHs3/5Ce17HxN16Ku6/vZq/X4M3Xv7MMA3FDVqlUdlv3dt2+fihcvbj+2c+dOdezYMc0xV3CbRMno0aP1999/67nnntPEiROVJ08e1ahRQ8OHD9ecOXNcHR4yYfIyqXdIR00e8bXmfRwmg9GoMZ++Lkl66fF39MG8Abrn/kCHa57v2ULXY+I075MfFXc9Tg/WraDuA9pkeQxA+kxeJr0xrKM+HP615qb0w9CUfvhis3f04fy0/fCFXi0UGxOnudPS9rXMjmXmnvtL6elnG2pQ18kym71VMriInmz/yO2+XcDt8C4EXO9Ovgsze9/1GtJBn09apC8/WKLEBKvqN62ujt0ev2PPAbmHwX1m0nAQHR0tHx+fNBUhTZo00bvvvqs//vhDtWvX1pdffqkGDZKXs2/evLmee+45denSRUFBQZo/f75at3bdvFwGm83mFnWctWvX1qJFi1S6dGnVrl1by5Ytk5eXl5o3b64dO3bkuL29l1dkfRJuq8uXrioi/KQqPFBG+f3zuTocuFCVQi217wp90BUuX7qqiH9O6v6qZVTAhf3wxOGzunQhSlUeulfe3m6Tk89VKhdsybvQBXgXIhXvQte5k+9C3nfurXLB7C9d64nylXnJKe3GHJufo/MrVKigNWvW2CdjbdKkiYYNG6ZmzZqlOffbb7/Ve++9p7x58yp//vxasGCBihQpIkmaPHmyZs6cKR8fH5UpU0bffPON8uTJ899v6Ba4TW8uUaKEtm7dqtKlS0tKXs7r0KFDDjPfwr0VKlxAtR6hLBhwpUKFC6iWG5TnB5croeByLO+O3Id3IeB6d/JdyPsOruSsOUpyav/+/Q7ba9euzfDc5557Tg0aNNDhw4dVq1Yt5cv3bzLzrbfeUqtWrXTu3DnVrl3bKfOkZJfbJEr+97//6Y033tDChQsVGxurcePG6a+//tKECRNcHRoAAAAAAG7FXRIlORUcHJzhPKTly5dX+fLl73BEablNoqRRo0ZasWKFVq5cqUqVKqlEiRL63//+x0SuAAAAAADgjnGbRIkklSlTRr169XJ1GAAAAAAAuDWDweDqEO5ablOrc+7cOfXp00fr1q2TJLVt21avvfaaLly44OLIAAAAAABAbuE2iZLhw4fL29tbFStWlCR9+OGHCggI0MiRI10cGQAAAAAA7sbopA/cZujNtm3btHLlShUvXlySdM899+itt95Sy5Z395JOAAAAAADklKdO5uoJ3ObJBgUF6Y8//nDYt3nzZpUqVcpFEQEAAAAAgNzGbSpKQkJC9Prrr+vHH39UcHCwTp06pa1bt+rTTz91dWgAAAAAALgVKkqcx22ebL169bRixQrVrl1bNptNNWvWVFhYmOrVq+fq0AAAAAAAQC7hNhUlUvLwm549e7o6DAAAAAAA3JrBfeoe7jpu82TXr1+vqKgoV4cBAAAAAIDbMxiMTvnAjRIlo0aN0p49e1wdBgAAAAAAyMXcJlHy0ksvae7cuUpMTHR1KAAAAAAAuDUqSpzHbeYoKViwoK5evap27dqpc+fOyps3r/1YmzZtXBcYAAAAAADINdwmUbJ48WJ5e3vL399fK1eutO83GAwkSgAAAAAAuAHVH87jNomS+fPnuzoEAAAAAAA8gkEGV4dw13LLFJTFYpHNZlNSUpKrQwEAAAAAALmI2yRKoqOjNXz4cNWvX18PPvig9u/fr0aNGrESDgAAAAAAN2EyV+dxm6cwbNgwnTp1SuPHj5evr6/y58+vrl276t1333V1aAAAAAAAIJdwmzlK/vjjD4WFhalkyZIyGo0yGAxq27atPvnkE1eHBgAAAACAW6H6w3nc5smWK1dOixcvlpS80o3BYNDWrVt13333uTgyAAAAAADcC0NvnMdtKkqGDx+u1157Td99951iYmLUv39/nT59Wp999pmrQwMAAAAAALmEyxMlFy5c0NatW2WxWDRz5kwdPnxYZ8+eVYkSJdS4cWPlz5/f1SECAAAAAOBmqP5wFpcmSjZu3Ki+ffsqKChIXl5eOnLkiEaMGKHXXnvNlWEBAAAAAIBcyqWJkkmTJmnYsGHq2LGjJOn3339X//791a5dO1eGBQAAAACAW2M+Eedx6ZONiIjQY489Zt9+5JFHFB8fr/Pnz7swKgAAAAAAkFu5tKLEarUqT548Dvvy5Mkjq9XqoogAAAAAAHB/VJQ4j0sTJTabTY899pgMBoN939WrV9WqVSsZjf/+Q9+yZYsrwgMAAAAAwC0ZmMzVaVyaKJk3b54rvx4AAAAAAMCBSxMlderUceXXAwAAAADgkRh64zw8WQAAAAAAgBQurSgBAAAAAAA5d+Ncn7i9SJQAAAAAAOBhGHrjPDxZAAAAAACAFFSUAAAAAADgYVge2Hl4sgAAAAAAACmoKAEAAAAAwMMwR4nzkCgBAAAAAMDDkChxHp4sAAAAAABACipKAAAAAADwMEzm6jw8WQAAAAAAgBRUlAAAAAAA4GmYo8RpSJQAAAAAAOBhmMzVeXiyAAAAAAAAKagoAQAAAADAwxgMBleHcNeiogQAAAAAACAFFSUAAAAAAHgYlgd2Hp4sAAAAAADIsQMHDqh9+/aqXbu2JkyYIJvNlun5CQkJmjBhgho3bqwGDRpoypQpSkxMlCTZbDaNHDlSderUUa1atTR06FDFxcXdidtI466tKKlSqKWrQwBytcoF6YOAq/EuBFyLdyEAZ3L1qjcWi0W9evVSgwYNNHnyZIWGhmrx4sVq3759htdMmzZNGzZs0JdffimLxaI333xTNptN/fv317Jly3TkyBEtWbJE0dHRGjZsmGbMmKF+/frdwbtKdtcmSrquX+fqEIBca06jR/XKht9cHQaQq81q2Jh3IeBCvAsB15vVsLGrQ3AuF0/mun79ekVHRyskJES+vr4aMGCARo8enWmiZNmyZQoJCVH58uUlSd26ddN3332n/v37a/fu3WrevLkCAwMlSc2aNdOhQ4fuyL3cjKE3AAAAAABAUnKlSHR0tMPHYrGkOS88PFzVq1eXr6+vJKlChQqKiIjItO3Lly+rZMmS9m2TySSTySRJKl++vMLCwnTx4kWdOnVKP/30k+rXr38b7yz7SJQAAAAAAOBpjM75zJgxQzVr1nT4zJgxI83XR0dHKygoyL5tMBhkNBoVFRWVYciVK1fWmjVrJElWq1XLli2zJ0M6duyomJgYPfLII2rSpIkCAwPVtm3bW38+/8FdO/QGAAAAAADkTM+ePdWtWzeHfWazOc15JpMpzX4fHx/FxcXJ398/3bZHjhypnj176u+//9bx48d15swZTZw4UZI0b948FShQQL/++qsMBoNGjBihiRMnaujQobfpzrKPihIAAAAAADyNweCUj9lslp+fn8MnvUSJv7+/IiMjHfbFxMTI29s7w5ArVqyotWvXKiQkRPnz51e7du0UHBwsSQoLC1P37t1VqlQplSxZUgMHDtQPP/xwe59ZNpEoAQAAAADA0zgpUZJdVatW1c6dO+3bJ06ckMViybCaJJXJZFJsbKyOHDmiPn362PcnJSXp0qVL9u0LFy7IarVm/3ncRgy9AQAAAAAAOVK7dm1FR0dr0aJFat++vWbMmKH69evLZDLp6tWrypcvn32i1ptNnTpV3bp1U/Hixe37atWqpS+++EImk0kJCQn64osv1KRJkzt1Ow5IlAAAAAAA4GlcPD7Ey8tLoaGhGjhwoCZOnCij0aj58+dLSk6iLF26VJUqVUpz3ZYtWxQeHq4pU6Y47O/fv7+io6M1adIkxcTEqEGDBnr77bfvyL3cjEQJAAAAAADIsaZNm2rVqlXau3evqlevrkKFCkmS9u/fn+E1derU0caNG9PsL1CggH1iV1cjUQIAAAAAgIex5WA+EWcqWrSoGjdu7OowbisSJQAAAAAAeBr3yJPclVj1BgAAAAAAIAUVJQAAAAAAeBojJSXOQkUJAAAAAABACipKAAAAAADwNG4ymevdiEQJAAAAAACehjyJ0zD0BgAAAAAAIAUVJQAAAAAAeBomc3UaKkoAAAAAAABSUFECAAAAAICnYTJXpyFRAgAAAACApyFP4jQMvQEAAAAAAEhBRQkAAAAAAJ6GyVydhooSAAAAAACAFFSUAAAAAADgaSgocRoqSgAAAAAAAFJQUQIAAAAAgIexsTyw07hNRYnVatW8efP0999/S5LeeecdffHFF7JarS6ODAAAAAAAN2M0OOcD90mUjBkzRgsWLJCXV3KRS506dfTjjz9q0qRJLo4MAAAAAADkFm6TKPn55581bdo0VapUSZLUunVrffDBB1q+fLmLIwMAAAAAwM0YnPSB+yRKfH19FRkZ6bDvypUrMpvNLooIAAAAAADkNm4zmevLL7+sfv36qUuXLgoODtapU6c0d+5cvfrqq64ODQAAAAAA98Jkrk7jNomSrl27qkiRIlqyZImWLl2qkiVLKiQkRE899ZSrQwMAAAAAwL0w8arTuE2iRJJatmypli1bujoMAAAAAACQS7lVogQAAAAAAGQDBSVO4zaTuQIAAAAAALiaSytKQkJCNGrUKPn4+CgkJCTD88aNG3cHowIAAAAAwM0xmavTuDRREhgYKEPKP9zAwEBXhgIAAAAAgOcgUeI0Lk2U9OnTJ92/BwAAAAAAcAUmcwUAAAAAwNMw46jT8GgBAAAAAABSuE2iZPfu3bLZbA77du3apcmTJ7soIgAAAAAA3JTB4JwP3CdR8uyzzyomJsZhX9GiRTVnzhzXBAQAAAAAgLsyOOkD90mU3FxNIkn79+9XgQIFXBANAAAAAADIjVw+mWvFihVlMBhkMBhUu3Zth2N58uTRmDFjXBQZAAAAAADuyWak/MNZXJ4oWbNmjWw2mx5//HEtXbpUfn5+kiSj0aiiRYvKy8vlIQIAAAAAgFzC5VmIwMBASZK3t7cCAwPtiRIAAAAAAJABJl51GpcnSlLt3r3b1SHgP7h+6pQOzZ6juAsXVKxBA5Xp0F6GTDpuUmKiji9ZqkvbtspmtapYw4YKbtlSBpPJfs61QxE6NGeOaoQ6Dr/aNWq0rp86Zd8u1qCB7n25iw7Nmq0Lmzal+a4a48YqT5Eit+EuAfcWc+qUDs2eq9jzF1S84SMqm2U/tOrYkiW6uHWbbFarijdsqNKtnnboh1cPRejg7Lmq+d67DtfuGPnuTf3wEd3XtUuWx4C7Ge9CwLV4DwK4XdwmUWKxWLR06VJ16NBBV65c0WeffSar1arXX39dRYsWdXV4yERSQoLCP56mglWq6P4er+nId9/pwh9/qNgjj2R4zcmwFbqyZ48q9esnW2Ki9k+fLtmk0m2ekSRFHzum/Z9+KqPZ7HCdNT5ecRcuqNaHH9hfYoaU4Vn3vPC8ynZ+1n7utYgIHf1ugXwCAm73LQNuJykhQf98/Mm//fDb73T+9z9UvEHG/fBEWJiu/L1XVfq/qaTERO3/bIYkm8qk9sOjxxT+yWfp9EOL4i5cUJ3J76fph5kdA+5mvAsB1+I9iFyJghKncZtVb4YMGaIFCxZIkt577z1FRETo6NGjGjp0qIsjQ1au7NmjxNhYlenUUXmKFVPptm11fuPGTK+5sHmTglu3Ut5SpZSvdGmVevwJXd65U1LyfwDu//QzlWjyWJrrYk6cUN6gIHnnzy+vvHnllTevTCkvL5OPj32fV968OrN6tYJat5LB6Db/mgNOc3nPXlmvx+qeTh3lW6yoyrRro3Mbf8/0mvObNiv4meR+6Fe6tEo98bgid+ySlNwPwz+drpLp9cPjx5UvKDDdfpjZMeBuxrsQcC3eg8iVjAbnfOA+FSXr1q3T0qVLZbPZtHHjRq1Zs0bR0dFq0aKFq0NDFmJOnFT+cuVk8vGRJOUNCtL102cyvSYxOlo+AYXt2wajQUr5jziDyaQHhg5R3PnzOn/TCy76yBFZLl/W1rcGyGa1qkidOir7bCcZvb1vOu+o4i9eUpGbVlIC7lY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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 9
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-06-12T13:15:49.262350Z",
     "start_time": "2025-06-12T13:15:49.258371Z"
    }
   },
   "cell_type": "code",
   "source": "",
   "id": "4f9247d45dcb535d",
   "outputs": [],
   "execution_count": null
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-06-12T13:15:49.731375Z",
     "start_time": "2025-06-12T13:15:49.280350Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from matplotlib.ticker import FuncFormatter  # 新增导入\n",
    "\n",
    "# 设置中文显示\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.rcParams['axes.unicode_minus'] = False\n",
    "\n",
    "# 创建数据集（新增SVM行）\n",
    "metrics = ['Accuracy', 'Precision', 'Recall', 'F1-score']\n",
    "models = ['Perceptron', 'Logistic', 'MLP', 'CNN', 'SVM']\n",
    "\n",
    "data = np.array([\n",
    "    [0.8811, 0.8810, 0.8811, 0.8808],    # Perceptron\n",
    "    [0.9157, 0.9155, 0.9157, 0.9155],    # Logistic\n",
    "    [0.9740, 0.9741, 0.9740, 0.9740],    # MLP\n",
    "    [0.9897, 0.9897, 0.9897, 0.9897],    # CNN\n",
    "    [0.9810, 0.9809, 0.9809, 0.9809]     # SVM\n",
    "])\n",
    "\n",
    "# 创建DataFrame\n",
    "df = pd.DataFrame(data, index=models, columns=metrics)\n",
    "\n",
    "# 绘制热度图\n",
    "plt.figure(figsize=(12, 7))\n",
    "ax = sns.heatmap(df, \n",
    "            annot=True, \n",
    "            fmt=\".2%\",  # 修改格式为百分比\n",
    "            cmap=\"YlGnBu\", \n",
    "            vmin=0.85, \n",
    "            vmax=1.0,\n",
    "            linewidths=0.5,\n",
    "            cbar_kws={'label': '性能得分', 'shrink': 0.8})\n",
    "\n",
    "# 设置colorbar为百分比格式\n",
    "cbar = ax.collections[0].colorbar\n",
    "cbar.ax.yaxis.set_major_formatter(FuncFormatter(lambda x, pos: f\"{x:.0%}\"))\n",
    "\n",
    "ax.set_title('模型性能对比热度图', fontsize=16, pad=20)\n",
    "plt.xlabel('评估指标', fontsize=12)\n",
    "plt.ylabel('模型类型', fontsize=12)\n",
    "plt.xticks(rotation=45, ha='right')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ],
   "id": "c67166e998b334ab",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1200x700 with 2 Axes>"
      ],
      "image/png": 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Fi8vLy+uO9wMAAOQMJEoAAPfUjBkzZDKZlD9/frm7u+uNN97QW2+9pXXr1lkSFh4eHrf8Yens7Jxh2I7JZNKYMWO0ceNGNW3aVGXKlLEcS6/CSEhIsLT16tVLvXr1UlRUlI4ePWpZdeXfSw43b95cefLkUenSpa0SJZIUHBysDRs2KC4uzjJ5bGYroSQlJSkhIUFGozFDBUR6IuDgwYNWc4WkTzKafv62bdt08uRJS9XMnXh5eenrr7/WCy+8oMGDB6tp06Yym8164oknJEkFCxZUVFSUPvvsMzVv3jxLfWZXQEBAls/9/PPPVbhwYXl5eemjjz7SiRMnMiyr6+TkpISEBJUoUUKzZs3SgQMH1LNnT0k3khNBQUGaMWOG6tevbzWnTHqi5OZhL/Hx8UpJSbGqxvm39CE4d5Kamqq//vpLf/zxh7Zu3apt27YpICBAY8aM0cMPP6yPPvpI77zzjmUFp0cffdSy7DMAAMi5SJQAAO6Z8PBwff/992rYsKEiIyMVFRWlVq1aWeakKFasmCTp+eefv20/lStXtvz1qVOn9OKLLyoiIkIPPfSQhg0bZnWum5ubChUqlOkQirNnz+rZZ5+VdGNS0H8PkShSpIjat29/yxiMRqOmTZuWYX4UKeOqNyNGjNALL7xg1ZaeHFmyZIlV1cKhQ4ck/TNfy6pVqzRv3jyrCo0zZ85o2rRpGjRoUKaTt3p7e+vrr79Whw4dtGLFChUtWtQyBMbLy0u9e/fWqFGj9P3336tbt263vMb7oVSpUlb7NyecEhISNGzYMHl7e2vu3Ln69ddfNWzYMJ0+fVqenp5as2aN6tevr88++0w7duywmislfSUhHx8fqz779u1rGZaUmfLly2c5/s8++0xbtmxRhQoV9O6776patWoaPny42rdvr6lTp+rIkSP68ccftXbtWu3YsUMtWrTIct8AAMAxkSgBANwTSUlJGjBggOLj4zVgwADL8I30JYLz5cunpKQkq+EgCxcu1AcffKAFCxZYVQr8exjFQw89pOeee047d+7Uxx9/nGG52EGDBumRRx7Ra6+9psGDB1st0VqxYkU988wzyps3rzp06JBhYtQ7qVatmvr162cZ2nHzqjdJSUmKj49XuXLlbtlH+tLDt5JeXeHh4aHQ0FB9//33Wrx4sQwGg4oVK6bXXnst088FBASoU6dO+uijj+Ti4qKEhATLsJAOHTroiy++0PTp0/Xiiy9aVdLYQ/rcJPv377eqJEpOTtZbb72lsLAwjR49Wv7+/mrfvr2KFCmiWrVq6fDhw1qyZIni4uIUHx+fIbGVPrTGz89PkZGRWrp0qYxGY4ahODfbunWrihUrdsf5Z5ycnDRy5EglJiZakmy//vqrrl27pvfee0/jxo1T06ZNNWbMGI0cOVJnz5695STFAAAg5yBRAgC4JxITE5UnTx61bdtWwcHBVsfy5cunixcvymQyyWg0WiosLl68KOlGFUT6/BFms1kpKSmKj4+3/Djt16+fzGazEhISlJSUJBcXlwyVCRcvXsx0vokxY8YoMTHxrpIFjz32mB577DHLflZXvfm3Ww29SZd+Ha1bt1ZYWJiCgoL0xhtv6Nlnn5W/v/8t+42JidGMGTPk4+OjU6dOaezYsRo5cqSkG8mXdu3aafbs2dqzZ4/VNdyNU6dOKU+ePHf9+bVr1+rLL7+UJL344ouSblSDvPnmm9q8ebPatWtnWfVG+mcy30GDBuno0aNau3atqlevnmES4PQhU0WLFtWVK1c0ceJEeXp6KiYmRs7OzpkuLRwREWFZJScr/r3086lTp1S7dm398ssv+u233zRjxgwlJyfLxcVFLi4uGapnAABAzkSiBABwT3h7e2vSpEmWFVNu9sknn2jx4sWZHstsuIKzs7PVMJXQ0NA7TiD65ptv6s0338z02E8//WRZUeV+2r59u1UCJzQ0NNPzateurREjRqhatWqZzodys/Hjx+vKlSv67rvv9OOPP2revHlq0KCBJZnQuXNnvfzyyypcuPBdx37y5ElNmTJFy5cvtyQ6bicuLi7TuWc6duwoPz8/1a5d25JEc3d3V61ateTs7GxJ8NwsX758Gj16tJydna1WTfp3fK6uripUqJAKFy6sv/76S5I0btw4zZkzR1OmTFGlSpUs56evetOrVy+r9qwwm8167bXXdOHCBdWpU0dNmjTRxx9/nGHYDwAAyPlIlAAA7hmj0ah8+fJlemzw4MEaNGiQXFxc5OzsrKNHj+rll19WixYttHPnTgUFBWnSpEmWyVz/PTmrdGPOjx49esjV1VUuLi5ydXW1HDt69KiWLl2q1q1bW030mpqaKpPJJJPJlGHIzv2Svozxnbz77rtZ7nPJkiVasGCBnn/+edWpU0dly5bV9u3bNWzYMFWtWlX+/v4qVKjQ3Yasv//+27LkckpKimrWrKmAgABL4ioziYmJatiwoR5//HGNGTPGMgxIulGJERERYZW0OXv2rLp3767u3bvLYDDoypUrWrRokZ5//nnLKjdTpkzRpEmTNH/+/AwTwErSH3/8oXLlymVIoPTv31+bN29W//79NXfuXBUuXFh79uzRiBEjVL9+ffXr1++213/zZMLpbYMHD9bGjRu1bt06bdy4Ue+//74ef/xxffLJJ1bXm+5OSw8DAADHRKIEAHBf/HsYSWRkpEaNGiV/f3+999572rFjh/r06aOxY8dqzJgxVkmQdKVKldJbb72Vad/r1q3T0qVL1aRJEzVr1izbsaUvMZz+5720YcMGq/kyfvvttywlRUwmk15//XX179/fqvph/fr1evfdd1WxYkVLP/7+/ho8eLDefvttTZgwQWPHjs12nLt375YkLV68WN9//72cnJzUuHFj9ejRwzK57q+//ipJGZJYkrRlyxZdu3ZNBw8ezJA0mDx5sv744w898cQTqlatmn7++WcNGjRIU6ZMsazWs3fvXn300UdKSUlRr169JEnt27fXV199pREjRmjBggVWCZGwsDBdunRJTz/9dIZYPDw89Pnnn+uFF17Qiy++qN69e2vcuHEqW7asPv300zsuCZxZosTFxUWNGzdW48aN9d577+m3337TTz/9JB8fn0yTJLfqBwAAOD4SJQAAm8gs6WA2m7Vu3TqNGzdOcXFx+vbbb+Xj46MmTZqoX79++vzzzxUeHq4xY8YoKCjovsWavlxs+p8mk0lnz56V0WiUq6ur5Yd1+ior0dHRunz5sqQbE5KaTCb5+vparVCT/iO5UKFCVnOU3GquD7PZbDXkJiwsTFu2bFHBggUtiZJ58+Zp1KhRKlq0qKZNm2ZVZdGuXTvt3bvXsqzuzdKTG7ca1nPu3DnLea1bt1bv3r2tVglKvxbpxrCfbdu2WfpKTk7WqlWrJN2YSPbftm3bph07dujpp59WtWrVJEmPP/643N3dNWfOHEuipFGjRipWrJhmz56tbt26yWg0qmDBgnr11Vc1adIkLVy40GoekwULFlj6yszDDz+sIUOG6O2339a7774rX19fjR079pbLUv9bSkqKYmJi9NVXX932vPQE0s3nHTlyxHJfAABAzkOiBABgEykpKZZkwfHjx7Vo0SJt2LBBx44dU9WqVfX1119b/RDv27evjEajPv74YzVv3lytW7dWt27dFB8fr0WLFt12JZNTp05JujEkZd++fZmek5SUJJPJpMaNG6tBgwZWx0wmk+UcSbpw4YKaN29+y2vLbOjGoEGDrFaouVU1QXpCIl16smPp0qVWc6jMnTtXktSkSRNJN5IzixcvVpEiRTRz5swMQ5wMBoNGjx6d4fu+++47Xbx4UZs2bZKkTCc4laQ+ffrozJkz6tatmx555JFMz2nRooXWrVunrVu3asaMGVbH3N3d1a5dO6ulk5OTkzV27Fi5urpqwIABlnY/Pz81a9ZMS5YsUXh4uAICAuTk5KRnn31WH3/8sX755RdLpUi3bt30/fff67PPPlPLli3l6empqKgoLViwQIGBgapdu7al34iICB0+fFh//PGHNm3apL///lt58uRRmTJltGvXLrVq1UqlS5dWpUqVVLJkSQUGBipv3rzKmzevSpcubeknJSVF165d08SJEzO9D1lFRQkAADkTiRIAgE1cv35d8fHxkqQCBQpo3bp1MpvNGj16tNq3b5/p8IfXXntNFSpU0Pjx4/XXX3+pcOHC2rx5sxYtWiQ3N7fbDpnIkyeP9u7dq71792Z6PD1REhgYeMtESfqf+fLl04cffmhZavZ235ve77/nRkm//pu/49VXX9WePXsUHByshx56SJLUrFkzrVixQkOGDLE632AwqHnz5mrUqJGkG8mFGTNmKDY2NlvzrYSHh2vGjBkyGAyqXbt2pkNVJFmSVLfj7u6epUld0x09elQmk0kdOnSwWj1Gkp566imdPHlSV69eVUBAgCTpmWee0ZkzZ6xWj/Hw8FCfPn0UERFhmfMjOjpa1atXV/Xq1WUwGDRixAgtW7ZMcXFxkm78s/D444+rZ8+eaty4sYxGo86fP69169Zpy5YtWrduna5evWr5juHDh2dIlBQtWlQbNmzI8rX+29ChQ7V48WIqSgAAyKEMZlsMyAYA4CYRERHy9/e/4/wQ0o1hKFFRUbddHjcnSkxMlNFozNKqNvfK+fPnFRYWpooVK9rlfqZPzJuVIS9307ezs7OuXLmiGTNmqEKFCnrkkUeyNGzr9OnTCgsL04kTJ9S5c2erYUwnT56U2WxWiRIl7nnMAADA8ZEoAQAAAAAASHPn/60HAAAAAACQS5AoAQAAAAAASEOiBAAAAAAAIA2JEgAAAAAAgDQkSgAAAAAAANKQKAEAAAAAAEhDogQAAAAAACANiRIAAAAAAIA0JEoAAAAAAADSkCgBAAAAAABIQ6IEAAAAAAAgDYkSAAAAAACANCRKAAAAAAAA0pAoAQAAAAAASEOiBAAAAAAAIA2JEgAAAAAAgDQkSgAAAAAAANKQKAEAAAAAAEhDogQAAAAAACANiRIAAAAAAIA0JEoAAAAAAADSkCgBAAAAAABIQ6IEAAAAAAAgDYkSAAAAAACANCRKAAAAAAAA0rjYOwBbORi1wt4hALlWhbytdOgqzyBgT+XztOJdCNgR70LA/srnaWXvEJBDUVECAAAAAACQhkQJAAAAAABAGhIlAAAAAAAAaUiUAAAAAAAApCFRAgAAAAAAkIZECQAAAAAAQBoSJQAAAAAAAGlIlAAAAAAAAKQhUQIAAAAAAJCGRAkAAAAAAEAaEiUAAAAAAABpSJQAAAAAAACkIVECAAAAAACQhkQJAAAAAABAGhIlAAAAAAAAaUiUAAAAAAAApCFRAgAAAAAAkIZECQAAAAAAQBoSJQAAAAAAAGlIlAAAAAAAAKRxsXcA6fbu3auPP/5YFy5ckNlstjq2fv16O0UFAAAAAAByE4dJlPzvf/9T1apV1atXL7m6uto7HAAAAAAAkAs5TKIkOjpaAwYMUNGiRe0dCgAAAAAAyKUcZo6Srl27avLkyUpOTrZ3KAAAAAAAIJdymIqSs2fPatOmTWrUqJGqVKkiLy8vy7GxY8faMTIAAAAAAJBbOEyipGjRonrxxRftHQYAAAAAAMjFHCZR0rdvX8tfR0ZGyt/f347RAAAAAACA3Mhh5igxmUwaO3asqlatqrp166pq1aoaP368TCaTvUMDAAAAAAC5hMMkSsaPH68///xT06dP12+//abp06drz549+vDDD+0dGgAAAAAAyCUcJlGycuVKjRs3To8++qjy58+vRx99VGPHjtXPP/9s79AAAAAAAEAu4TCJEj8/P504ccKq7cSJE/Lz87NTRAAAAAAAILdxmMlcBwwYoEGDBql169YKCgrSmTNntHz5co0fP97eoQEAAAAAgFzCYSpKmjVrppkzZ0qSdu7cKYPBoNmzZ+upp56yc2QAAAAAACC3cJiKEkmqVKmSKlWqZO8wAAAAAABALuUwFSXHjh1TQkKCvcMAAAAAAAC5mMMkSrp06aJ9+/bZOwwAAAAAAJCLOUyipG3btlq0aJG9wwAAAAAAALmYwyRKHnvsMZ06dUqvvfaaNm3apJ07d1o2AAAAAACA+8FhJnN95513JEmXLl3S+++/b2k3GAxav369vcICAAAAAAC5iMMkSjZs2GDvEAAAAAAAQC7nMENvAAAAAAAA7M1hEiUrV65USkqKVduuXbv0v//9z04RAQAAAACA3MZhEiWDBg1SfHy8VVtQUJB++eUXO0UEAAAAAAByG7vPUXL+/HlJktls1oULF+Tl5WXZ37RpkwICAuwZHgAAAAAAyEXsnihp1KiRDAaDDAaDWrdubWk3GAwqVqyYRo4cacfoAAAAAABAbmL3REloaKgkKTg4WDt37pSPj4+dI8KDJOJilPIXymvvMAAAsBvehQAAZI/DzFFSokQJOTs72zsM3KW1S7erx9Mj1bHBUA17/UuFn7ty2/asuHAmQp2fejfLx/7ccVhdmg7TTzPWSZLOnbqkg3uP3+UVAbgXzGazIi5etXcYwH3BuxDAzXgPAjmTwyRKVq1aJU9PT3uHgbsQfjZCC75dq6EfdtPn84YoIDCfJo/68ZbtWerz3BWNHvi1Yq/FZ/nY2qXb9XpIB61btkOStO3X/XqsUeX/foFADrF26Xa92nqknq8/VO/e9CMts/asuHAmQp2ezPgj7a89x9T3+fHq/NQwLZ27ydK+4eedernJu9rw805J0r4dR3TpQuR/vDLA8fEuBOzvXr8Hb/WuM5vNmjr+J3V68l291PgdTRr5gxITkiTxHgTuFbPZrPDwcLt9v8MkSlJSUjRz5kx17txZLVu2VJcuXTR37twMSwbD8Rw/ck5lHnlIDwcHqkBAXjVqVVMXzkbcsj0rxr41XU+2qZ2tY7HXrqt46SIym81KTDDJyckgV6PdR5cB98WFsxGaP32tQiZ00+T5QxRQNJ8+H/njLduzIvzcFY16M+MPseioWI1961vVe7Kqxn3zhjb/skcHdh2VJK1asFVvfdBJqxZslST9vf+EylcpeW8vFnBAvAsB+7rX78Hbves2rtqtc6cua+KsgRozra/OHL+ohTPXS+I9iNwnMjJSjRo10tmzZy1tR44cUfv27VWjRg2NHz9eZrPZcuyPP/5Q8+bNVatWLc2YMcPSvnjxYtWoUUOLFy+WJG3dutWqz/vNYRIlH3zwgb7//ns1atRIffv2VcOGDfXtt99q3Lhx9g4NdxBUopAO7ArTiSPnFBcbr18WblXlmmVu2Z4Vb0/srseeyPz/gN3qmIenm6KjYiVJW9b9qbpNqtz1NQE5zYnD1j/GGre+8WPsVu1ZMWbQdD2VyQ+xzb/sUd4CvurQ/UkVKVZAHbo/qXXLb/zf65hr1/VItVKKuXZdERejlK9gnnt5mYDD4l0I2Ne9fg/e7l0XdvC0HmtUSQUL++uhUoVVs8EjCk/rk/cgcpPIyEj16tVL586ds7SZTCb16tVLFSpU0MKFC3Xs2DEtWrTIcv7rr7+uli1bat68eVq+fLm2b98uSZozZ44+/fRTzZkzR5K0Z88eVa9e/f5fVBqHSZT8/PPPmjx5srp27armzZvrlVde0eTJk7V06VJ7h4Y7CCoRoDqNKmtQ54/Vqcm7OvLXKXXp1/qW7VlRqEi+bB+r26SKhvX6Qo8+Vk6Xzkfetg/gQWOLH2nvfNw905L9k2HnVbFaKRkMBklS6QrFdCz0Rsbfw9NNF05flqeXm35bs1f1nqp67y4ScGC8CwH7utfvwdu964qVDNCmX3br6pUYXboQqS1r91r65D2I3GTgwIFq1aqVVdvmzZsVGxurkJAQFStWTAMHDtRPP/0kSVq2bJkKFiyoPn36qHjx4urdu7flWHR0tGrWrKno6GhduHBBAQEB9/16/s1hajGLFi2qS5cuqUyZf/7FdfHiRbvfINxZ2MHT2rXloMZ984aKFi+oJbN/1eiB36jHoLaZtn/4bX/LS+deqvfUo3r0sXI6d/KSIi5e1Xt9p0iS3v7oVbm5u97z7wMcSVDJGz/GBnb6WJJUqIi/xn/bX355vTNtz4pCRfLp0vmM46qvxyUosEQhy76nl5uiLl+TJNV7qqoGvDxRHV99SkmmFHl4uv3XSwNyBN6FgH3d6/fg7d51TZ6ppV8W/a5XWoyQJNWoV15PtLzxf755D+JBYDKZZDKZrNqMRqOMRqNV26hRoxQUFKQPPvjA0hYaGqrKlSvLw8NDklS2bFkdO3ZMknT48GHVqlXL8v6rVKmSJk6cKEny8vLSqVOn5O3trRUrVujFF1+02fVlhcMkSooXL65+/frpySefVOHChXX27FmtX79ezZo10+TJkyVJffv2tXOUyMxva/eqbpOqKvPIQ5KkF3s11+rFv2vOlz9n2n4y7LxKlClqk1i8vD20Z1uoHg4OlI+flyTprz1HVe2xcjb5PsBRHEn7kTZ++o0fY4tn/6rRb36jHm+1zbT9wxl3/yPN2cXJas4DV6OrEhNuvEzbdW6kpu3qaO+2UPn4eemtLp+ocGB+DRz9sk1+FAKOgnchYF/3+j14u3fdih83y8vbQ18tfVcGgzRl7E+a+fkKvdL/ad6DuK88ir1gk34//N9jlt/g6fr27at+/fpZtQUFBWX4bGxsrAIDAy37BoNBTk5Oio6OVmxsrB5++GHLMW9vb126dEmS1LJlSz399NPq27evTCaTvLy87uUlZZvDDL1xc3NTs2bN5OzsrEuXLsloNKp58+YyGAw6d+6c1bgnOBZzqlnX0sZDS1L89UQlJiTJ3cMt0/bU1FSbxRITHSdvXw/Fxcar6EMFVfShgoqJjrPZ9wGOYsuavXr8yRs/xry8PfRSr+YKPxeh2V/8nGn7ybDzd/1d3r6eVs92wvVEubj+8x+TXt4eOn0sXOdOXVKFRx9WxKWrOnvi4n+6PsDR8S4E7Otevwdv967bvHqP2rzcUAUC8ip/obx6uXdLy0pTEu9B5Hw9e/bU7t27rbaePXtm6bPOzs4ZKk/c3NyUkJCQ4Vh6uyS99tpr2rFjh4oXL66qVauqXbt2evPNN60mgr2fHKaiZOzYsfYOAXepXJUS+nzkjyr5wyb5+fto3bIdyuPvo4YtquvzURnbHypVRNKNkkajm6tcXJzvWSybf9mjek89qiN/ndLl8ChJUqlyGTOdwIMmNdWs2Kv//BCKj0v7kebppujI2AztqSl3/yOtVLkg/bZmr2X/+OFz8i/ga9k/fTxcxR4O0PnTEQoqUUjXomIVE339rr8PyAl4FwL2da/fg7d715lTzZZJkyXpauQ1pab+82OO9yDuF4PBNnUPmQ2zySo/Pz+FhYVZtcXFxcnV1VV+fn6KjIzM0J7Ox8dHR44cUYECBVSzZk3t27dPx44dU6lSpe7uQv4Dh6koSUpK0tSpU9WhQwfVq1dPYWFhevbZZ3XmzBl7h4Y7qPNEJbXt3EjL5/2myaN+VFxMvIaM76o6jTJvT/+PwTdf+ki7tx66p7EkJ6fIL6+3Hnn0YZ0+Fq7Tx8L1SLX7/2AB91v5KiW0feMBLfthkzav3qOxg2coT74bP9Iya3+odNqPtNgEJSdnbxn2mvUrKHT/Ce3744iSk1O0eM6vqlq7rOX49l8PqPYTleTl466L5yMVcfGqvHw87un1Ao6GdyFgX/f6PXi7d125KiW1aOYGbVjxh9Ys3qZpHy5SzXrlLZ/lPYjcrGLFivrzzz8t+2fOnJHJZJKfn1+GY4cOHVKhQv/MBRQWFqYyZcro6tWrKlWqlIKCgnT16tX7F/y/GMz2qmW5ybvvvqsDBw7ohRde0IcffqilS5dq1qxZCgsL03fffZft/g5Grbj3QQLIkgp5W+nQVZ7B+8lsNmvBt+u0btkORUVcU7GHA9TnnQ4qUaZopu0ly94YO/pam9Hq/uYzqtWgYqb9XjofqZ5tP9DiHROt2n9Z9LumT1wid0+jvLw9NO6bN5Qnn49SklO0auHvavV8PV0Oj9LwPlNUODC/3v3kVTk5OUxuPlcon6cV70LAjngX3l+2eA/e6l0XFxOvbyYu1p7th5VwPUFVapVVn3c6yDePN+9BB1M+T6s7n5SDeT3UySb9xp2ana3zy5Ytq/Xr1yswMFDJycmqV6+e3nrrLbVv317vvvuuIiIiNHXqVEVGRqphw4aaOnWqatSooddff10PPfSQhg0bJkn64osv9Nprr+nHH39URESE9uzZo3fffVdly5a9QwT3nsMkSmrUqKGFCxeqWLFiqlGjhpYuXSoXFxc1bdpUe/fuvXMHN+E/DgH74T8Oc4eL56/o7MlLKl+lJLP6OyASJYB98S58MPCuy9lIlNyd/5IokaT169dr0KBBcnNzk5OTk2bPnm0ZPvPDDz/ogw8+kKenp3x8fDRv3jzlz59fycnJmjt3rjp37qzz58+rS5cuKlasmL7++mu7JBkdZo6SgIAA7dy5U8WKFZN0Y3bco0ePWs2YCwBwHIWK5FOhIvnsHQYAADbDuw6OzFZzlGTX4cOHrfYbN26stWvX6uDBg6pcubLy5s1rOfbCCy/o8ccf1/Hjx1W9enXL6jYuLi7q3LmzJKlIkSJau3bt/buATDhMouR///uf+vTpo/nz5ys+Pl5jx47V7t27NX78eHuHBgAAAACAQ3GURElmChQooIYNG2Z6LCgoKNOlhR2JwyRK6tevrxUrVmjVqlUqV66cAgIC9L///c/hbyAAAAAAAHhwOEyiRJIeeugh9erVy95hAAAAAADg0AwGg71DeGA5TK3OxYsX1bdvX23atEmS1LZtW/Xo0UOXL1+2c2QAAAAAACC3cJhEybBhw+Tq6qrg4GBJ0scffyx/f3+99957do4MAAAAAABH42SjDQ4z9GbXrl1atWqVChUqJEkqUaKE3nzzTbVq9WAv6QQAAAAAQHY58mSuOZ3D3NnAwED9/vvvVm3bt29XkSJF7BQRAAAAAADIbRymoiQkJESvv/66fv75ZwUFBencuXPauXOnvvzyS3uHBgAAAACAQ6GixHYc5s7WqVNHK1asUI0aNWQ2m1WtWjUtX75cderUsXdoAAAAAAAgl3CYihLpxvCbnj172jsMAAAAAAAcmsFx6h4eOA5zZzdv3qzo6Gh7hwEAAAAAgMMzGJxsssGBEiUjRozQX3/9Ze8wAAAAAABALuYwiZJOnTpp5syZSk5OtncoAAAAAAA4NCpKbMdh5ijJkyePrl27pnbt2qljx47y9PS0HGvTpo39AgMAAAAAALmGwyRKFi1aJFdXV/n5+WnVqlWWdoPBQKIEAAAAAIB/ofrDdhwmUTJ79mx7hwAAAAAAQI5gkMHeITywHDIFZTKZZDablZqaau9QAAAAAABALuIwiZLY2FgNGzZMjz32mKpUqaLDhw+rfv36rIQDAAAAAMBNmMzVdhzmLrz99ts6d+6cxo0bJw8PD/n4+Khr164aOXKkvUMDAAAAAAC5hMPMUfL7779r+fLlKly4sJycnGQwGNS2bVt98cUX9g4NAAAAAACHQvWH7TjMnS1ZsqQWLVok6cZKNwaDQTt37lTp0qXtHBkAAAAAAI6FoTe24zAVJcOGDVOPHj30448/Ki4uTgMGDND58+c1ZcoUe4cGAAAAAAByCbsnSi5fvqydO3fKZDJp+vTpOn78uMLDwxUQEKCGDRvKx8fH3iECAAAAAOBgqP6wFbsmSrZs2aJ+/fopMDBQLi4uOnHihIYPH64ePXrYMywAAAAAAJBL2TVRMmHCBL399tt67rnnJElbt27VgAED1K5dO3uGBQAAAACAQ2M+Edux6509duyYnnjiCct+3bp1lZiYqEuXLtkxKgAAAAAAkFvZtaIkJSVF7u7uVm3u7u5KSUmxU0QAAAAAADg+Kkpsx66JErPZrCeeeEIGg8HSdu3aNbVu3VpOTv/8Tf/jjz/sER4AAAAAAA7JwGSuNmPXRMmsWbPs+fUAAAAAAABW7JooqVmzpj2/HgAAAACAHImhN7bDnQUAAAAAAEhj14oSAAAAAACQff+e6xP3FokSAAAAAAByGIbe2A53FgAAAAAAIA0VJQAAAAAA5DAsD2w73FkAAAAAAIA0VJQAAAAAAJDDMEeJ7ZAoAQAAAAAghyFRYjvcWQAAAAAAgDRUlAAAAAAAkMMwmavtcGcBAAAAAADSUFECAAAAAEBOwxwlNkOiBAAAAACAHIbJXG2HOwsAAAAAAJCGihIAAAAAAHIYg8Fg7xAeWFSUAAAAAACA++7ChQv2DiFTJEoAAAAAAMhhDHKyyZZVCxcuVKtWrVS9enUNHDhQkZGRkqQFCxaoQYMGqly5sjp16qQzZ85IkkJDQ1WvXj0NHz5cknTt2jWtXr363t+Ye4BECQAAAAAAyLLff/9do0ePVkhIiJYtW6bY2Fj17dtXp0+f1hdffKEvv/xSq1atUlBQkIYOHSpJWrp0qV5//XXt2LFDcXFxWr58uVq1amXnK8ncAztHSYW8jnnDgdyifB6eQcDeeBcC9sW7EIAt2XPVmyVLlqhdu3aqW7euJGnw4MFq2bKl/vrrL1WuXFkVKlSQJLVv3179+/eXJEVHR6t+/frKnz+/oqOjdeXKFeXPn99u13A7D2yipOvmTfYOAci1vqvfQN1+22jvMIBc7dt6DXkXAnbEuxCwv2/rNbR3CLZlx8lco6KiVKZMGcu+k9ONpE3JkiW1fft2/f333woMDNTcuXMtyRQvLy9dvXpV0dHROnDggGrXrm2X2LOCoTcAAAAAAECSZDKZFBsba7WZTCarc8qXL6+NGzcqNTVVkrR48WJVrFhRwcHBatq0qdq0aaPq1avrzz//1JAhQyRJTz31lEJCQlS4cGGFhoaqZs2a9/3asopECQAAAAAAOY2TbbZp06apWrVqVtu0adOsvrp79+5KTU1V27Zt9fzzz+urr77Syy+/rP379+vXX3/V/PnztWvXLrVq1Uo9evSQ2WxWjRo1tGXLFo0cOVIFCxbUm2++qXbt2uny5cu2v1fZRKIEAAAAAABIknr27Kndu3dbbT179rQ6x9fXV3PnztWkSZNUtmxZlSxZUq1bt9aKFSvUsmVLVa5cWT4+PhowYIDOnDmj0NBQSZK3t7dWrlyp4OBghYeHq0aNGlqzZo09LvO2Htg5SgAAAAAAeGDZaI4So9Eoo9GYpXMLFiyotWvXatSoUXJ2dlZqaqqioqIsx+Pi4hQfH6+UlBRJUnJysmU/KChIpUuX1sWLF21yHf8FiRIAAAAAAHIaO07mmm727NkqWbKkmjRpIkmqXr26hg4dqu+++0758uXTggULVKBAAZUtW1aStG7dOjVp0kQGg0Hh4eE6c+aMQ658Q6IEAAAAAABkS3R0tKZPn66vv/7a0ta0aVMdO3ZMM2fO1OXLl1W6dGlNnjxZrq6ukqTz58+rWbNmSk1Nlaurq1auXKlZs2bZ6xJuiUQJAAAAAAA5jZ1nHPXz89OOHTus2gwGg/r06aM+ffpk+plu3bpJurGc8PTp020e491iMlcAAAAAAIA0VJQAAAAAAJDDmB1gjpIHFYkSAAAAAAByGvIkNsPQGwAAAAAAgDRUlAAAAAAAkNM4UVJiK1SUAAAAAAAApKGiBAAAAACAnIbJXG2GRAkAAAAAADkNeRKbYegNAAAAAABAGipKAAAAAADIaZjM1WaoKAEAAAAAAEhDRQkAAAAAADkNk7naDIkSAAAAAAByGvIkNsPQGwAAAAAAgDRUlAAAAAAAkNMwmavNUFECAAAAAACQhooSAAAAAAByGgpKbIaKEgAAAAAAgDRUlAAAAAAAkMOYWR7YZhymoiQlJUWzZs3SgQMHJEnvvvuuvv76a6WkpNg5MgAAAAAAHIyTwTYbHCdRMmrUKM2bN08uLjeKXGrWrKmff/5ZEyZMsHNkAAAAAAAgt3CYRMkvv/yiyZMnq1y5cpKkp59+WhMnTtSyZcvsHBkAAAAAAA7GYKMNjpMo8fDwUGRkpFXb1atXZTQa7RQRAAAAAADIbRxmMtcuXbqof//+6ty5s4KCgnTu3DnNnDlTr776qr1DAwAAAADAsTCZq804TKKka9euyp8/vxYvXqwlS5aocOHCCgkJUYsWLewdGgAAAAAAjoWJV23GYRIlktSqVSu1atXK3mEAAAAAAIBcyqESJQAAAAAAIAsoKLEZh5nMFQAAAAAAwN7sWlESEhKiESNGyM3NTSEhIbc8b+zYsfcxKgAAAAAAHByTudqMXRMlRYsWlSHtb27RokXtGQoAAAAAADkHiRKbsWuipG/fvpn+NQAAAAAAgD0wmSsAAAAAADkNM47aDLcWAAAAAAAgjcMkSvbv3y+z2WzVtm/fPn3yySd2iggAAAAAAAdlMNhmg+MkSp5//nnFxcVZtRUoUEDfffedfQICAAAAAMBRGWy0wXESJTdXk0jS4cOH5evra4doAAAAAABAbmT3yVyDg4NlMBhkMBhUo0YNq2Pu7u4aNWqUnSIDAAAAAMAxmZ0o/7AVuydK1q9fL7PZrCeffFJLliyRt7e3JMnJyUkFChSQi4vdQwQAAAAAALmE3bMQRYsWlSS5urqqaNGilkQJ8F+ZzWaZoq7KzT+vvUMBcq3EyEi5+fvbOwwg1+JdCNgf70LYDBOv2ozdEyXp9u/fb+8Q8B9c2rpV59eslSkqSnkeeUQlXugoVx8fSVJSTIwOfDBG5d8aJPf8+bPUX+jkyYra988/E37lglV+4ECdWbZMZ5evyHB++bcGKfHKFZ2cN1/Fn++ggo89puhDh+RkNPIfh8gVLm7ZqvNr1ikxKkp5Kz6iki90lKvPjcRzUkys9n0wRo+8NTDLz+Chz7/I8Aw+MujN2x6LOnhIR77+RkWaNFFQqxa6Hh6u2JOnVLB2rXt4pYDj4l0I2BfvQgD3isMkSkwmk5YsWaJnn31WV69e1ZQpU5SSkqLXX39dBQoUsHd4uI2rhw7pxA8/qmzv1+VRqJCOf/+9Dn85RY8MGaykmBiFfj5ZiVeuZKvP2JOnVHnEezLmvfEfdgZnZ0lS0ebNVbhJE8t5iVeu6NAnn8orKEinFvykMj1f0+lFi1XwsccUc/SYgp55+t5dKOCgrh76W8d/mKdyvXvJIyBAx+Z8r9Avp6jikP8pKSZWhz6frMSI7D+DVd4fLrebnsHbHbu4+TeV6txJJ+YvUFCrFrqye4+KPvXkPbpKwLHxLgTsi3chciUKSmzGYVa9GTJkiObNmydJ+uCDD3Ts2DGdPHlSQ4cOtXNkuJPL27ar4GOPKU/58nLLl08PPfusYo4eVVJcnMK+/lr5a9XMVn+JUVGSzPIsWlQunp5y8fSUs5ubJMnJ1dXS5uLpqfBfN6pw48Zy8fRU8vU4+ZYpo+TrcUqMjLT8hyXwoLu0bbsK1a2jPBXKyy2fv4o/117Xwo4qKTZOh7/6WgVq3t0z6JXJM3i7Y8lxcfIKCpTMUkqiSQaDk5xcXe/x1QKOiXchYF+8C5ErORlss8FxKko2bdqkJUuWyGw2a8uWLVq/fr1iY2PVvHlze4eGO0iOjZVnYFHLvsHpRv7NYDCoZKfOci+QXyd/nJfl/mJPnJQ51azd/xus5OvXlbdyJZV86SW5eHlZnWe6elWRe/fq0bFjJEnObu5KuHRJzu4eivjjDwU0bPjfLw7IAZJjYuVZtMg/DenPoJOTSnXuJPcC+XUim8+gUs3a+b8hSo67Lv/KlfTwyy/Kxcvrtsec3d2VdC1GkhSxc6fy16h+D68ScGy8CwH74l0I4F5ymIoSLy8vXb58WX/88YeCgoLk7e2t8+fPM7lrDuBVrJii9u+XOTVVknTp99/lVby4XDw95V4ga2NA/y0hPFxegYEKfqOfHgkZqsSICJ1etDjDeeGbNil/zZpydneXJOWvWVP73h+pfI8+KnNysqUdeNB5PRSkqP0H/nkGt26Td/HicvH0uKtnMD48XJ6BgSr/Rl9VenuoEiIidHLRkjsey1+jug58+JHyVnxECRFX7uq7gZyKdyFgX7wLkSsZDLbZ4DgVJd27d1fnzp1lMBj0/vvvKzQ0VP369VPHjh3tHRruoEjTp3TtyBHtHzVaTkajYo8fV6lur9x1f0VbNFfRFv9UEj307LM6PGWKSnZ62dJmTk3Vpd9+U/mBA//5XPNmKtSgvq4ePCgXLy/tH/2B3AsWUOkePWTggccDrGjTp3TtSJj2jfpATq6uijl+QqW73/0zGNiiuQL/9QwWf669Qr+cqlKdXrrtsQK1aipvxYqKDw9XYmSk/vroY0lSuTf6ytlovPsLBHIA3oWAffEuBHAvOUyipGvXrqpfv76MRqMCAwN16dIlffjhh6pbt669Q8MduHh66pEhgxV/6ZIurF6jlOvXlb/WvZvZ29XHR8mxcUpNSrKM8YwODZWLl7c8ixSxOtfF01PXz52X0c9XvmXKKPbEccVfuJDhPOBB4uLpqYpD/qf4i5d0bs1aJV+PV4FszodwO64+vhmewVsdc/H0UNSBv+T9UDG5pFUERoceln+livcsHsAR8S4E7It3IXIl8t824zBDbySpZMmSCgwMlCQVLFiQJEkOY/Tz05W9e1WsXVvL2Oy7cWTaV7oWFmbZjzl+XK6+vlYvpSu7dsv/0aoZPnv93Hl5Fi2i5Lg4eRYpLLf8BZQcG3fXsQA5iTFPHkXu2auH2v+3ZzB06le6FnbUsh9z7JjlGbzdMUlKio2Vi5enkuPj5REQII+AACXH8Qwi9+BdCNgX70LkKg/AZK4XLly4r9+XVQ6VKEHOFr7hV3kEBMi/asb/aMtMcny8UpOTM7R7Fi2qk/Pm61pYmCL37tXpRYtVqEEDq3OuHvxLfmXKZvhs5N498q9aVc4enkq4HCFTVKScPT3u7oKAHObChg3yCCikfFWrZOn8G89gSoZ2r8CiOjFvvq6FHdWVvX/q1KIlCmhY/47HJOny9j9UoFZNuXh4KPHKFSVeuSIXD55B5B68CwH74l0I3D8LFy5Uq1atVL16dQ0cOFCRkZFWxydMmKBevXpZ9kNDQ1WvXj0NHz5cknTt2jWtXr36vsacVSRKcE8kx8Xp/OrVKv7cc1n+zP73R+rqgQMZ2os0ayrPwED9/dkkHf/+exVq2FCBLVtYjidcuiTT1Wh5lyhu9TlzSoqcPTzk5OIi/yqVFbFzpwwurpQaI1dIjovTuV/WqHiHrD+Df44YpahMnsGizZrJMzBQBz+dpGNzvlfAEw0UlPYM3u6YdOM5dPXxkW9wWV0/d17Xz52XX3DGH3LAg4h3IWBfvAuR69ixouT333/X6NGjFRISomXLlik2NlZ9+/a1HA8NDdXcuXP1zjvvWNqWLl2q119/XTt27FBcXJyWL1+uVq1a3fPbci8YzGaz2V5f3rlzZ02bNk0eHh7q1KnTLScZmzVrVrb77rp5038ND8Bd+q5+A3X7baO9wwBytW/rNeRdCNgR70LA/r6t19DeIdjUw90X2KTfY9PvnGwcPHiwfHx8NGzYMEnS0aNH1bJlS+3YsUO+vr7q2LGj6tatq/79+1s+8/bbb6t169aaPHmyJkyYoJ9++klvvPGGTa7hv7LrZK5t27aVa9pYvnbt2tkzFAAAAAAAcgyzHSdzjYqKUpkyZSz7TmlzAjk7O+uHH37QkSNH1KFDB61fv1716tWT0WiUl5eXrl69qujoaB04cEC1a9e2V/h3ZPdESWZ/DQAAAAAAbsNGE6+aTCaZTCarNqPRKOO/lrguX768Nm7cqG7dusnJyUmLFy9WxYoV5eTkpM8//1xBQUE6f/68li5dqilTpmjOnDl66qmn1KNHD9WoUUOhoaFW1SaOxmGWBwYAAAAAAPY1bdo0TZ482aqtb9++6tevn2W/e/fu2rlzp9q2bSt3d3f9+eefGj9+vNauXav4+HjNnDlT/v7+Sk5OVuvWrbV06VI9//zz2rJli2JiYrRx40a9+eabOnXqlKZNm6YCBQrc78u8LYeZzPXXX3/V9evX7R0GAAAAAACOz2CwydazZ0/t3r3bauvZs6fVV/v6+mru3LmaNGmSypYtq5IlS6p169YKDw9X5cqV5e/vL0lycXFR2bJlderUKUmSt7e3Vq5cqeDgYIWHh6tGjRpas2bNfb91d+IwiZKRI0cqIiJC+/btU1RUlKX9yy+/VO3atbVq1So7RgcAAAAAwIPPaDTK29vbavv3sJt/K1iwoNauXatBgwbJ2dlZAQEBSkxMtDrn/PnzKlSokCQpOTlZ8fHxSklJUVBQkEqXLq2rV6/a+pKyzWESJc2bN9czzzyjPn36qFGjRpaVbr799lsNHz5cU6ZMsXOEAAAAAAA4CDsuD5xu9uzZKlmypJo0aSJJatCggY4ePaoffvhB4eHhmjVrlkJDQ/XUU09JktatW6cmTZrIx8dH4eHhOnPmjHx9fe/5rfmvHCZRsnz5ck2dOlVbtmzR0qVL9dFHH+nKlSu6fv266tSpoxMnTtg7RAAAAAAAHIOTjbYsio6O1vTp0zVkyBBLW968efXVV19pyZIlatq0qWbNmqVPP/1UhQsXlnSjuiQ4OFilS5eWq6urVq5caUmyOBKHmczVaDTq4sWLSklJ0cWLF+Xs7Kzo6Gj5+voqOTlZLi4OEyoAAAAAALman5+fduzYkaG9WrVqmjdvXqaf6datm6QbywlPnz7dpvH9Fw6TfRg9erSGDBmiIUOGyNfXV5UrV9Zbb70ld3d3ffLJJ1ZrNAMAAAAAkKsZbLM8MBwoUVKnTh1t3rxZkZGRypMnj5KTk7Vjxw49+uij+uabb/Tiiy/aO0QAAAAAAPCAc5hESTqz2ayDBw+qaNGiqlevniSpf//+do4KAAAAAAAHks2JV5F1DpMoiYmJ0dChQ7V+/XoZjUYlJSXpySef1JgxY+Tt7W3v8AAAAAAAcBhmht7YjMOsevP+++8rNTVVmzZt0v79+7Vx40YlJydrxIgR9g4NAAAAAADkEg5TUfLbb79p4cKFKlSokCSpUKFCCgkJUfv27e0cGQAAAAAADsZhyh4ePA5zawsXLqzt27dbtW3fvl1FihSxU0QAAAAAACC3cZiKknfeeUevvfaaVq1apaCgIJ05c0Z79+7VV199Ze/QAAAAAABwLEzmajMOU1FSo0YNrVq1SrVq1ZLBYFCtWrW0cuVKeXh42Ds0AAAAAACQSzhMRYkkBQQE6LXXXrPsX7x4Uc8++6z+/vtvO0YFAAAAAICDYdUbm3GoRElmzGazvUMAAAAAAMCxMPTGZhxm6M2tGMiSAQAAAACA+8ThK0oAAAAAAMBNqCmwGbsmStq0aXPbipGkpKT7GA0AAAAAAMjt7Joo6dKliz2/HgAAAACAHMnMHCU2Y9dESdu2be359QAAAAAA5EwkSmzG4SdzBQAAAAAAuF+YzBUAAAAAgJyGFWJthooSAAAAAACANFSUAAAAAACQ01D2YDMkSgAAAAAAyGkYemMz5KAAAAAAAADSUFECAAAAAEBOw/LANkNFCQAAAAAAQBoqSgAAAAAAyGmoKLEZEiUAAAAAAOQwZiZztRmG3gAAAAAAAKShogQAAAAAgJyGsgeb4dYCAAAAAACkoaIEAAAAAICchjlKbIaKEgAAAAAAgDRUlAAAAAAAkNOwPLDNkCgBAAAAACCnIVFiMwy9AQAAAAAASENFCQAAAAAAOQ0FJTZDRQkAAAAAAEAaKkoAAAAAAMhhzMxRYjMkSgAAAAAAyGkMJEpshaE3AAAAAAAAaagoAQAAAAAgp2Hojc1QUQIAAAAAAJDGYDabzfYOAgAAAAAAZF2xSZts0u/pNxrYpN+c5IEdelP6yen2DgHItcLWducZBOyM5xCwL55BwP7C1na3dwg25cT4EJvh1gIAAAAAAKR5YCtKAAAAAAB4ULE6sO1QUQIAAAAAAO67Cxcu2DuETJEoAQAAAAAghzEYbLNl1cKFC9WqVStVr15dAwcOVGRkZIZzunfvrkWLFkmStmzZolq1amnKlCmSpOPHj2vnzp335F7cayRKAAAAAADIYQwGg022rPj99981evRohYSEaNmyZYqNjVXfvn2tzlm2bJm2bNli2Z8/f75Gjx6tBQsWSJLWrFmjZs2a3bsbcg+RKAEAAAAAAFm2ZMkStWvXTnXr1lWRIkU0ePBg7d69W1evXpUkXb16VePHj1eJEiUsn4mOjlZwcLAkKT4+Xk5OTjIajfYI/46YzBUAAAAAgBzGnpO5RkVFqUyZMpZ9p7S1ip2dnSVJ48ePV5MmTZSYmGg5x8vLS1euXJEkrVy5Us2bN7+PEWcPFSUAAAAAAECSZDKZFBsba7WZTCarc8qXL6+NGzcqNTVVkrR48WJVrFhRPj4+2r59u7Zt26b//e9/Vp9p0aKFXn75ZdWvX19nz55VUFDQfbum7KKiBAAAAACAHMZWFSXTpk3T5MmTrdr69u2rfv36Wfa7d++unTt3qm3btnJ3d9eff/6p8ePHKzExUe+9955GjBghb29vqz5atWqlBg0a6Pjx4zp//ry6dOli+T53d3fbXMxdIlECAAAAAEAOY7DR+JCePXvqlVdesWq7eS4RX19fzZ07V6dOndL06dN17do1tW7dWpMmTdIjjzyihg0bZtq3j4+PNm/erAoVKihv3rySpB07dqhBgwY2uZa7RaIEAAAAAABIupEUyeokqwULFtTatWs1atQoOTs7a/ny5YqKilL16tUlSQkJCVq1apX279+vESNGKCoqSr6+vrp27ZploteoqCibXcvdIlECAAAAAEAOY8/JXNPNnj1bJUuWVJMmTSRJc+fOVXJysuX4hx9+qMqVK6tt27aSpOXLl6t169b6888/df78eUlSxYoV73/gd8BkrgAAAAAAIFuio6M1ffp0DRkyxNIWEBCgwMBAy+bp6am8efPK399fkpScnCx/f3/VrFlTYWFhCgsLU61atex1CbdERQkAAAAAADmMk50rSvz8/LRjx47bnjNu3Dir/W7dukmSvL29tWjRIpvF9l9RUQIAAAAAAJCGihIAAAAAAHIYR5ij5EFFogQAAAAAgByGRIntMPQGAAAAAAAgDRUlAAAAAADkMAZKSmyGihIAAAAAAIA0VJQAAAAAAJDDGCh7sBmb3dpTp07prbfeslX3AAAAAADkWgaDbTZksaIkJCREJ0+elKura4ZjTk5O8vX1Ve/evRUcHGxpj4+P17p16+5dpAAAAAAAADaWpURJrVq1VKZMGbm6umaYMCYlJUWLFy/WBx98oLFjx6ply5basWOHjEajjEajTYIGAAAAACA3o/rDdrKUKGnTps1tj1+/fl2XL1+W0WhUYmKi3Nzc7kVsAAAAAAAA91WWJ3Pt0KGD3NzcLBUlZrNZiYmJmjBhgnr16iVJioiIkIuLC8sUAQAAAABgQ/zstp0sJ0qaNm0qo9EoJ6cb87+mpKQoMTFRPj4+NgsOAAAAAABk5ESixMrMmTN1/fp1vf766/+5ryytehMREaGyZcuqU6dOeumll5SamqozZ86oR48e8vf3/89BAAAAAAAA3I2zZ8/q008/VWJi4j3pL0sVJSdPntRXX32lxx9/XJIUExOjS5cuSbpRWZKUlKTJkyfrp59+UkpKih5//HGlpqbekwABAAAAAIA1ht7cEBkZqddee03VqlWTt7e3Vq5cqcKFCysgIEAFCxaUs7NztvvMUqLE1dVVf/zxh8qVK2fV/u/9/v37a8CAARo1apSGDRumixcvavLkydkOCAAAAAAA4E5CQ0M1YMAAFS5cWJ9++qmqV6+uKlWq6NKlS7p8+bJSU1NVrFgxjRgxQrVq1cpyv1meo+SRRx5RSEiIzGazVqxYoVOnTqlv375KTU2VyWRS+fLllZKSotGjR6tp06Y6fvw4iRIAAAAAAGwgN1eUREVF6YsvvtCiRYvUtWtX9e3bV2azWZI0d+5cy9yqV65c0Zw5czRx4kTNnz8/y/1nOVHi6+uratWqSZL27NmjmJgYy366iIiILH8xAAAAAAC4O4ZcPJur2WxWQkKCVqxYoSJFiki6MS3IzSvw5suXT02aNNH27duz1X+WEyUHDx5Ur1695OrqqlOnTikpKUkLFixQvXr1FBAQYAksJSUlWwEAAAAAAABklb+/v0aPHp3psZuTJWXLltUPP/yQrf6ztOqNJOXJk0c1atTQI488ovz58+v69euaOnWqnnzySY0ZM0bJyckymUwym80ymUzZCgIAAAAAAGSdwWCbLafYtWuXkpKSrNrMZrNq1qypl156SVOnTlVkZKRcXLJcH2KRpURJcnKy/P391b17d/Xs2VOPPvqoKleurPXr12vkyJH68ccf1bt3b/n4+KhXr16WAFn5BgAAAAAA3EupqakaPny4mjZtqmXLlkm6kYMwGAyaOXOmnnvuOe3cuVPNmzfXnj17st1/llIrJUuW1MCBAy37SUlJlqqRtm3bKj4+Xtu3b5e7u7sGDBggSUpISLhnaxgDAAAAAIB/5KTqj3vNyclJy5Yt0/Lly/XJJ59o3rx5ev/992U2m/Xwww+rfPnyatOmjebPn6+ePXtq9uzZCg4OznL/WUqU5M2bVzVq1LDsd+nSxarE5YUXXtALL7xgNRaobNmy2rhxY5YDAQAAAAAAWZObEyWS5OLiorZt21qmA3nxxRc1evRoubm5Wc7p0KGDLl68qJCQEC1cuNCyGs6dZHmOkn/z9/dXoUKFLPsGgyHDhCkuLi7Kly/f3XQPAAAAAABwR97e3hozZoz69eunUaNG6dy5c1bHX3vtNeXNm1exsbFZ7jPbiZJLly7pgw8+sOzHxMQoJSVFx48fV4MGDazOnTp1qn777bfsfgUAAAAAALgNJ4NttpyqU6dOmjVrlooWLWrV7ubmpunTp8vX1zfLfWU7URIXF6f58+db9t955x29+eabMhgMunr1qtW5ixcv1qpVq7L7FQAAAAAAANlSuXLlTNtvHgFzJ1lKlERGRmrQoEFKTEyUq6urjEajJOnnn3/W2rVr1aZNG6t2Sdq7d69OnTqlDh06ZCsgAAAAAABwe7l9eeDM7Nq1S6dOncow2iW7sjSZ6/Hjx7V9+3Z16dJFb7/9tgwGg6KjozV69Gj17NlTjRo10rlz56yyNDNmzFD9+vVVpUqV/xQgAAAAAADAv7Vs2VKurq4yGAxKTU2Vv7+/nnrqKV29elUpKSm6dOmSzGazvLy85O3tna2+s1RRUr16dS1fvlzOzs4KCQmRJI0fP16FChVSv379Mpy/du1a/fbbb3r77bezFQwAAAAAALgzg5NttpwiOTlZEyZM0PXr1/XRRx/p1KlTcnJy0ogRI3T16lXL6rz16tXT+PHjs9V3lm+Dv7+/ZsyYodGjR8tsNqtUqVIaO3asnJ2drc7bsmWL3n77bX344YcqXrz4HftNTEzUvn37tGvXrmzNQgsAAAAAQG6V24feGI1GlS5d2vJnusmTJ6tQoUJav369NmzYoHHjxmn+/Pkym81Z7jtLQ2+OHj2qQ4cOycXFRVFRUUpOTlZAQICOHz+u0NBQJSYm6ujRo4qNjdUbb7yh0aNH68knn7xjv3/99Zd69+6tuLg4S8JlwoQJ/3k8EQAAAAAAyH1unri1QoUKGjZsmMxmc5Yndc1SomTnzp364osv5OzsrJSUFCUkJOj999+Xm5ubTCaTSpUqpStXrig1NVX58uVT4cKFs/Tlo0ePVocOHdS3b19J0qJFi/TOO+9oy5YtWfo8cDt+PkaZklIVn5Bs71CAXMndzVnuRhddjUm0dyhArsW7ELAvnkHYUnZXcsmNYmJiFB0drTZt2mTrc1kaevPCCy9oy5Yt2rRpk3788UeZzWb5+Pho5syZ2r59u+bMmaOvv/5anp6eevrpp9WlSxctXbr0jv0eOnRIzz33nGW/bdu2unr1qq5cuZKti4D9tW9aWj9/1U67F7+sT95uqLy+bmr3VGmFre2eYWv3VOk7d5jGx8uorT++oKKF/pl856Wny2nb/Be1YdZzql3ln6TcqP519dsPHRVc0l+S9HyL4Ht3gYCDu5/PoCQ1q1dcsyc0t2rr/WIV7fjpJdV9tIgkqdUTD8vTw/W/XxyQQ/AuBOyLZxDIXS5evKiQkBDLn+nSh9hs3bpVzZs318yZM7Pdd5YqStItW7ZMMTEx8vHxUePGjdW9e3f99NNP8vf3l8FgkIuLi/r166eqVauqX79+KlGihCpVqnTL/pKSkuTl5WXZNxgM8vT0lMlkyvaFwH4eq1pE7/aurb7vr9fxM9Ea2b+uvhjRRF0Gr9Laracs53l5uGjplDbadSA8y30Pea2mCubztOw/Xr2ohr5WUwM++FWR0QmaOLSB2vVZpqTkVNWqUlhTvv9TzzR+WMdOX5Wzs4HsPXKF+/kMSjeew/H/q68DRyKs2p9rXkbvfrJFz7cM1tY951WkoJfOX2LuKeQOvAsB++IZRG6U2wtKhgwZIqPRqMcff1ypqamqV6+erly5oqSkJCUmJqpQoUL64IMP7mpqjywnSpYvX66QkBC1aNFCBoNBISEhOnXqlIYPH67Jkydbnfv444+rffv2GjNmjH788cdb9mk2m/Xiiy9aTQgbGxurHj16yNX1n/8LuXjx4uxcE+6zNk+W0qI1Ydq657wkafxXf2jV9Pby9HBRdMw/Sa+Xni6nNVtP6fSFmCz1W6NigBrXKabI6ARL24utymnx2jCt33ZakrTu99N68vGH9Nuuc4qIjNfxs9F6pEx+Na1XXGu2nLx3Fwk4sPv5DBYr4qP3+tbR98v+VqXgAhk+E3osUi8/U15VyxfU3kOX/uOVATkH70LAvngGkRvl9kTJI488orJly0qSFixYoAYNGsjNzU1Go1FxcXEqVaqUSpUqdVd9Z2noTWxsrD744AMNGzZMAwYMsLR/8MEH2rZtmzZv3pzhM506ddK+fft04MCBW/Y7duxYvfLKK+rcubNl++CDD9S9e3erNji2vH7uunApzrKfknqj1Ckl5Z9ZhY2uzurStoKm/rAvS30aXZ00akBdjfpim67HJ1nag0v6a9veC5b9/Ycv65HS+RV3PUl+Pm7K4+um2OtJKlUsj46djv6vlwbkCPfzGbx6LVHt+izT0dNXM3zGYDAoX14PxcaZVK96Uf2269xdXhGQ8/AuBOyLZxDIXXbt2qVnn31WM2bMkMlk0vz589WuXTtt3bpVu3fv1qRJk7RlyxZt2bJFmzdv1vr167PVf5YqSry9vfXzzz8rX758On36tOLj4yVJ+fLl08svv6xJkybpk08+UUpKiuUzDz30kCpVqqQVK1aoYsWKmfbbtm3b235vcnKyDh8+nNVrgZ0cCruiJ2oHafpPB2Q2S+2eKq19oZcVe/2fF8rTjUpqX+glnbuYtTL8Xi9U1omz0Vq56YT+92oNS7u3l6vOhv/zfwBi45JUMJ+nYuJMOn85VuPeqq+Ppu9URGT8vbtAwMHdz2fwWuyth0Zu3HFG309soXHT/rj7iwFyKN6FgH3xDCI3ys0VJdWrV9fMmTMVEhKiv/76S999952mTZumgQMHKjg4WAEBAZZzU1JSlJycrMaNG2e5/ywPvcmXL58kyWQyKSkpSUlJSXJ1dVXbtm21c+dORUVFKSkpyeozVapU0d69e7MczM2uXLmiZ599Vn///fdd9wHb+2bBAdWoFKClU9ooITFFVcsX1FvjN1md07FVOX0+e0+W+nu4mJ9eaFVOz7y+JMOxlBSzTEn/JOQSk5Ll4XbjH+Me76yRl4erXmlfQcdPR2v9zOc0e+khfbfo4N1fHJAD3M9n8HZGfP67Ppq+U+2bltGho1e06pt22rTzLIkT5Aq8CwH74hkEcp9HH31UP/zwg3r06KHp06dr4MCBKliwoL777juNHz9efn5+d913tiZzlaRixYppyZIlljlEihcvrjlz5ig2NlbDhw+3Ove5557T66+/ftfBSf/MWAvHFRNn0osDf1axIj569bmK8vU2avmGY5bjxYr46KEivtq6O2tl+KMGPK5PZuzWpSvXMxyLjkmUfx53y76Xh1FJyalW5yQkpqhjq2BNmr1XA7o8yosJD7z7+QzeSVx8kny9jWpUO0gLfjmil1qX06SZe3SdiezwgONdCNgXzyByI6dcXFGSzt/fX3PmzJG7+41n8uWXX5a3t7d8fHz+U79ZmqPk34xGo4KDrZe5cnJykq+vr5599lmr9lKlSilPnjz/KUDWhs45Ll25rqfqFtdH03cpNfWfBFeLBiX1647TSk65c9KrSEFv1agYoCGv1dDuxS9r9+KXVaSgt1ZMa6vWT5TU/sOXVbVcIcv55Uv5Kzzin/GorRuV1PINx+Tn46Y9f10UeTbkJvfjGbyTBjWC9Nuus/LzcdOho1d0MeK6fH3c/tN1ATkJ70LAvngGkZs4GWyz5TQeHh5WeYM2bdrIySnbqQ4r2a4oyaorV65o/fr16tChg62+Ag6mc5sKOn4mWut+P2XVXr96oBatOZLhfB8vo+Lik6xeYhcj4tTw5XlW5/34SSsN+OBX/X3siuISkjWy/2NauPqIklNS9Vyzshr95XbLuQH5vXTxynXFxCaqTIm8uXrcHnKf+/EM3kmVcgX06cw9ala/hIoX9VV+fw/F3GZeE+BBw7sQsC+eQSB3uXTpkgoWLKh33nlHJUqU0KuvvipJOn36tIoVK6akpCS1b99e7dq1U9euXbPcb5YSJXPmzNHly5etluxN5+TkJD8/P7Vu3Vq+vr6W9vDwcI0ePfq2iZI2bdrctmLk5jlP4Lh8vY16tUNFdQ9ZbdXuZnRW5eACevfTLRk+s2dJJz3da7H+PhZpaUtJNWeYYCs5JVXhEXG6npCsDdtOq3n9Elr73XOSpG17z2t12rJrwSX99cf+cEnS/FVH9NHQBpq1mDJH5A736xm8nby+bjp1/pokadn6Y/pq9JPa9MdZxcXz73LkDrwLAfviGURu42TI3eVKhw4d0rvvvqtFixapfv36mjRpkh5//HGZTCb17t1bv/76qwwGg4YOHar//e9/2UqUGMxZmARkzJgxOn36tIxGY4Zjqamp2r17tx577DENHTpUb7/9tr744gudOXNGHTt21M6dO2/Z7+LFi2UwGG47D4nBYFCbNm2ydjX/UvrJ6dn+DHKOimXyy8PdxfIigmMJW9udZxCwM57DBx/vQsfGM/jg4xl0fGFru9s7BJtqujpj8u9eWN30cZv0awvdunXTgAEDVKlSJb333ntq3769KlWqpH79+qlJkyZ65plnJEmtW7fW8uXLs9xvlipK3n777dseHz9+vHbv3q3U1FRt2bJFTk5OMhgMd5xfJCQkRAaDQc7OzqpQoYLc3KzHsZvN5rtOlODBduBIhL1DAADArngXAvbFMwh7y4nzidxrPXv21JIlS1SpUiUlJiZa2nv37q3x48dbEiXJydlbWCDLc5RMnDjRKpFhNpuVmJioLl266LXXXlPevHkVEREhJycnubhkrdthw4bp2LFjCgsL0/Hjx+Xj46OyZcsqODhYZcuWVdmyZVW0aNFsXRAAAAAAAA+6/zZdac7XsWNHGY1GHTx4UEeOHNGhQ4fUvXt3dejQQW5ubtq7d686d+6sxMRERUdHZ6vvLCdKjhw5IqPRaKkSSU1NVWJiohISEhQUFGQ5Lzur1Lz00ktW+5cuXdKvv/6qVatWadKkSZIkb2/v2w7fAQAAAAAAucuAAQPk4eEhSTp+/LgmTJigggULauDAgZZ26UaOokiRItnqO0uJkqSkJI0dO1b+/v6SpI0bN+ry5ct67rnnsvVlN9u4caOOHj2qo0ePKiwsTOfOnVNgYKDKli2roUOHWqpLAAAAAADAPx6EyVwvXLigwoUL39Vna9euLUn68ssvNWPGDK1evVqTJ0+Wq6trhuWBAwMD1apVqyz3naVqnT///FNvvPGGZf+vv/7S5s2brc5ZtGiRhg0bptTUVA0aNEjjx4+/Y7+9evXSxIkTtXz5crm4uKh+/foqXbq0UlNTFRoaqqVLl2apHwAAAAAAcP8sXLhQrVq1UvXq1TVw4EBFRt5YPWrdunVq3Lixypcvr2eeeUbHjh2TJIWGhqpevXoaPny4JOnatWtavXr1LfvPim+++Ua//fabgoOD5e/vrzlz5ig1NVXffvutkpOT9e233yoxMVFffvlltvrNUkWJ0WjUkSNH1LlzZ0k3sj7Xr19X586dlZycrKSkJFWpUkV+fn6SpDx58mTI4GSmT58+2RqqAwAAAAAA7DuZ6++//67Ro0dr8uTJKlGihEaMGKG+fftq3LhxevvttzVixAjVrFlTo0aN0jvvvKMff/xRS5cu1euvv66ZM2cqLi5Oy5cvz1aVx8327Nmj559/Xh07drRM6+Hj46O+fftq0aJFlj/79++vChUqZKvvLM9RkidPHtWpU0eStGvXLl2+fFl16tRRSkqKkpKS1LZtW3l5eWnFihWWSVo3bdp02z779euXrWABAAAAAIB9LVmyRO3atVPdunUlSYMHD1bLli21Z88eDRo0SC1atJAkvfDCC+rZs6ckKTo6WvXr11f+/PkVHR2tK1euKH/+/Hf1/ekjWerXr6/hw4crJiZG0j9zpt78Z5MmTbLVf5YTJYGBgXr99dclSV999ZUOHz5s2U8XEfHPEllUigAAAAAAYBv2XPUmKipKZcqU+SeWtBEljRs3lo+Pj6X9xIkTeuihhyRJXl5eunr1qqKjo3XgwAHLHCN3w8nJSYsWLdLo0aPVu3dvxcbGymw2Kzo6Wh9//HGGPyVp4MCBWe8/qyeeO3dO3377rWbPnq19+/bp4sWLOnXqlNU5qampSk1NzfKXAwAAAACA7HMy2GYzmUyKjY212kwmk9V3ly9fXhs3brT8/l+8eLEqVqxolSQxmUyaMWOGOnbsKEl66qmnFBISosKFCys0NFQ1a9b8T9efN29eTZw4UY8++qhMJpMiIyPVvXt3+fn5qXfv3sqTJ4969+4tX19fubu7Z6vvLFeUXLt2TTt27FBycrJOnz6t8PBwNWvWTCVKlNDAgQPVpEkTJSUlyWw2Kzk5OdsXCQAAAAAA7GvatGmaPHmyVVvfvn2tps7o3r27du7cqbZt28rd3V1//vlnhoVYPv/8c3l4eFhWy61Ro4a2bNmimJgYbdy4UW+++aZOnTqladOmqUCBAncdb8+ePdW5c2d5eHhkGPWSLn2i2azKUkVJSkqKSpYsqWnTpmn69Olq27atGjVqpLVr16py5crq16+fvvzySxmNRlWtWlXJyckym80ym3P+ckUAAAAAADgag8Fsk61nz57avXu31ZY+z0g6X19fzZ07V5MmTVLZsmVVsmRJtW7d2nJ827Zt+v777zVx4kS5urpa2r29vbVy5UoFBwcrPDxcNWrU0Jo1a/7TfTCZTJo4caJlPzk5WQsWLLA63rJly2z1maVESf78+fXkk09afZHJZFJgYKDGjh2rjh07atmyZfLw8NDcuXPl7u6upKQkJSUlZSsYAAAAAABgP0ajUd7e3lab0WjM9NyCBQtq7dq1GjRokJydnSVJZ86c0aBBgzR8+HCVKlXK6vzk5GTFx8crJSVFQUFBKl26tK5evfqf4nVxcdHy5cst+2azWePGjbO6nn8na7LUZ1ZOKlasmLp27WrZf+KJJ1S1alXL/qBBg5ScnCxvb29LW0BAgMaMGZOtYAAAAAAAwJ3Zc3ngdLNnz1bJkiUtq8okJCSoV69eaty4sZ588knFxcVJkjw9PWUwGLRu3To1adJEBoNB4eHhOnPmzF2vfJPOycnJMpmsJLm6umZIjPz7eFZkeY4Sk8mkH374QV26dFHlypWtjqUnSOLj4zVp0iQNGTJEKSkpWrFihRo3biw3N7dsBQUAAAAAAG7NnqveSDeW+50+fbq+/vprS9uWLVt09OhRHT16VPPnz7e0r1+/XoGBgTp//ryaNWum1NRUubq6auXKlZo1a9ZdfX/jxo3l4eEhg8GgmJgYq6E/sbGxVvvZleVEicFg0KeffqouXbrolVdeUXJysgwGg8xms0wmk+bNmyej0ahVq1ZpyJAhWrZsmc6fP0+SBAAAAACAB4yfn5927Nhh1dakSRMdPnz4lp/p1q2bpBsVHtOnT/9P3//hhx/K3d1dTk5O6tKliyZMmCDpxtCbrl27Wu3fapLXW8lSEio1NVUuLi6W8pW//vpL3bt315kzZ9S9e3eFhYVJkpydnS3L8nz77bcaMWJEtoIBAAAAAAB35mQw22TLKapVq6YLFy4oNTVVzs7OCg4OVnBwsMqWLStJlv1y5cplu+8sJUq+++47lStXTjExMeratasMBoMaNmwoDw8PNWzY0DJpiyQlJSVpwIABCgkJUZUqVbIdEAAAAAAAwJ388ssvevPNNxUTE6Pu3btr4cKFunr1qoKDgy3npKamKjk5OVv9ZilR0qpVKy1ZskReXl4aPXp0puesXbtW27ZtU/78+fXWW2+pRYsW2QoEAAAAAABkjZPBNltO8tFHH2nNmjVasWKFChQooFWrVunkyZOaOXOm5Zzk5OQMq+/cSZbmKClYsKAKFiwoJycnBQYGZnrOZ599ZlnW5+zZs6pUqVK2AgEAAAAAAFlj78lcHcXy5cs1btw4Pfnkk/rmm28yHDcajfruu++y1WeWEiVfffWVfvjhB8XGxmr48OGZnrNixQpJUo0aNbRu3TpFR0frhRdeyFYwAAAAAAAAt3P16lWNGDFCbm5uio+PV+3atZWYmKiQkJAM56akpCgxMVGfffZZlvvPUqKkWbNmqlq1qnr16qUuXbpo1apVWr9+va5fv67169dbjfdxcXHRuHHj9Oyzz6pmzZp6+OGHsxwMAAAAAAC4s5w2TOZeMhqNqlKlioxGo5ycnJSQkCAPDw+ZzRkno01JSVFSUlK2+s9SoqRYsWIKCgqSwWDQww8/rOLFi2vy5Mny9/fX5MmTVbRoUUsAycnJMhqNev755zVhwgRNnTo1WwEBAAAAAADciqenp7p27SpJSkxMVL169eTh4aGHH35Yzz777H+eMzVLiRJJMplMqlOnjkwmkyZMmKDixYtLkqKjo7V+/XpJNyZJeeSRRyRJDRs21CeffKLr16/L09PzPwUJAAAAAAD+kZOW8rUlNzc3/fHHH4qMjNTff/8tPz+//9xnlud/cXNz0+eff65Tp05Zxv1s27ZNrVq10s8//6yYmBi5ublpxowZkqSiRYvqp59+IkkCAAAAAMA9xqo31vz9/VW3bl1L8cZ/kaWKks2bN+vixYtydXXVpUuXdO3aNS1ZskT79u1T1apV1ahRI0tVSTqz2azExERL5QkAAAAAAICjy1KiZNWqVdq2bZuMRqOSk5MVHh6uoUOH3ujAxUWHDx/OMGlKamqqkpKS1LFjx3sfNQAAAAAAuRjLA9tOlhIlY8eOtfz1sWPHNHr0aH3wwQdas2aNFi1apNTUVHXo0EHPPfecPDw8bBYsAAAAAACALd1VEsrJyUlFihRR165dtWzZMg0YMEAzZsxQmzZtFBUVda9jBAAAAAAA/+JkMNtkQzZWvUn38MMPa/r06VZtTZo0UfXq1RUZGam8efPes+AAAAAAAEBGOXniVUeX7UTJreTJk0d58uS5V90BAAAAAADcd/csUQIAAAAAAO4PKkpsh4lyAQAAAAAA0lBRAgAAAABADkPVg+1wbwEAAAAAANJQUQIAAAAAQA7DUr62Q6IEAAAAAIAchslcbYehNwAAAAAAAGmoKAEAAAAAIIeh6sF2uLcAAAAAAABpqCgBAAAAACCHYY4S2yFRAgAAAABADmNg1RubYegNAAAAAABAGipKAAAAAADIYRh6YztUlAAAAAAAAKShogQAAAAAgByGqgfbIVECAAAAAEAO48RkrjZDEgoAAAAAACANFSUAAAAAAOQwTOZqO1SUAAAAAAAApDGYzWYGNgEAAAAAkIO8v3edTfp9r2oTm/SbkzywQ28CyofYOwQg1wo/NJZnELAznkPAvngGAfsLPzTW3iHYlLO9A3iAMfQGAAAAAAAgzQNbUQIAAAAAwIOK5YFth4oSAAAAAACANFSUAAAAAACQw7A8sO1QUQIAAAAAAJCGihIAAAAAAHIYKkpsh0QJAAAAAAA5jDOJEpth6A0AAAAAAEAaKkoAAAAAAMhhGHpjO1SUAAAAAAAApKGiBAAAAACAHMbJYLZ3CP/ZhQsXVLhwYXuHkQEVJQAAAAAA5DBOBttsWbVw4UK1atVK1atX18CBAxUZGSlJOnLkiNq3b68aNWpo/PjxMptvJHS2bNmiWrVqacqUKZKk48ePa+fOnff8vtwLJEoAAAAAAECW/f777xo9erRCQkK0bNkyxcbGqm/fvjKZTOrVq5cqVKighQsX6tixY1q0aJEkaf78+Ro9erQWLFggSVqzZo2aNWtmz8u4JRIlAAAAAADkMM422rJiyZIlateunerWrasiRYpo8ODB2r17tzZu3KjY2FiFhISoWLFiGjhwoH766SdJUnR0tIKDgyVJ8fHxcnJyktFo/O83wgZIlAAAAAAAgCyLioqymlvEyelGauHIkSOqXLmyPDw8JElly5bVsWPHJEleXl66cuWKJGnlypVq3rz5fY4660iUAAAAAACQw9hqjhKTyaTY2FirzWQyWX13+fLltXHjRqWmpkqSFi9erIoVKyo2NlaBgYGW8wwGg5ycnBQdHa0WLVro5ZdfVv369XX27FkFBQXd1/uVHax6AwAAAABADmOrVW+mTZumyZMnW7X17dtX/fr1s+x3795dO3fuVNu2beXu7q4///xT48ePV1hYWIbhNG5ubkpISFCrVq3UoEEDHT9+XOfPn1eXLl0s3+fu7m6Ta7lbJEoAAAAAAIAkqWfPnnrllVes2m5Ofvj6+mru3Lk6deqUpk+frmvXrql169aaPn26wsLCrM6Ni4uTq6urJMnHx0ebN29WhQoVlDdvXknSjh071KBBAxteUfaRKAEAAAAAIIdxzsZSvtlhNBqzPMlqwYIFtXbtWo0aNUrOzs6qWLGiZVUbSTpz5oxMJpP8/Pwk3ZjbxNfXV9euXVOJEiUsbY6GOUoAAAAAAEC2zZ49WyVLllSTJk0kSTVq1FBsbKwWLlwo6cawmscee0zOzjfW01m+fLlat24tX19fnT9/XufPn5evr6/d4r8VEiUAAAAAAOQwtprMNauio6M1ffp0DRkyxNLm4uKi0aNHa9SoUapVq5bWr1+vt956y3I8OTlZ/v7+qlmzpsLCwhQWFqZatWrdy9tyTzD0BgAAAACAHCY7SQ1b8PPz044dOzK0N27cWGvXrtXBgwdVuXJly1wkktStWzdJkre3txYtWnTfYs0uEiUAAAAAAOCeKVCggBo2bGjvMO4aiRIAAAAAAHIYe1eUPMiYowQAAAAAACANFSUAAAAAAOQwzgazvUN4YJEoAQAAAAAgh2F4iO1wbwEAAAAAANJQUQIAAAAAQA7DZK62Q0UJAAAAAABAGipKAAAAAADIYagosR0qSgAAAAAAANJQUQIAAAAAQA7D8sC2Q6IEAAAAAIAchqE3tsPQGwAAAAAAgDRUlAAAAAAAkMNQUWI7VJQAAAAAAACkoaIEAAAAAIAchooS2yFRAgAAAABADuNMosRmGHoDAAAAAACQhooSAAAAAAByGCeD2d4hPLCoKAEAAAAAAEhDRQkAAAAAADkMVQ+2Q6IEAAAAAIAchlVvbMeuiZJGjRrJYLj9312DwaB169bdp4gAAAAAAEBuZtdESb9+/TK0paamauPGjdqwYYMMBoOaNm1qh8jwoChcyFcXLl6zdxhArsUzCNgfzyFgXzyDsBWWB7YduyZK2rZta/nra9euaf78+frhhx90/fp19ejRQy+88IIKFSpkxwiRVR3bVlOvro+rcCE/bfjtiN75YJkir17Xi+2ra1Dvxsqbx1N/HjirAe/+pNNno+7YX59u9fXSczXk5+uhZav2a9TEVboen6S3+jTWW32aZDi/XZevFFgkr0YObaXh41Zo/tI9avBYacUnmHgxIVfgGQTsj+cQsC+eQQD3it3nfwkNDdU777yjBg0aaOXKlerbt682bdqkAQMGkCTJIerVeVij326t4eN+VqO2n8nH203ffv6yHgry18DejdW172zVa/WxTp65os/GPHfH/l5sX12vdnpMfQbP09MvTVXVikEa/96NpNrnX29SmVrvW7ZGbT9TxJVYHfj7vLq9WEevDZyrbi/WkSTVfPQh/bHnlE2vHXAEPIOA/fEcAvbFM4jcyMlgtskGO1eUdOzYUfv27ZOzs7MaNWqk6tWrKyYmRj/++KPVeZ07d7ZThMiKDk8/qnlLdmvztqOSpJEfrdLm5W+qcoWi2rPvtA78fV6S9MOi3fr6kxfv2N9zzzyqaTO3aO+Bs5KkCV+s09SPOkqSEk3JSjQlW8595YU6+mr2VsXEJiqPn4d+33lcefw8VCTAT+fDo+/1pQIOiWcQsD+eQ8C+eAaRGzGZq+3YNVHi6uqq6tWrS5KioqK0du3aDOcYDAYSJQ7OP6+X/g4Lt+ynpKRKko6euKy6tR5WheDCOn02Ul1fqK3Nvx+9Y3/58nrq3IWrVv2lpGTMbBYq4KMWTcqrxlMTJEmx1xNV8qH8iolLVNsWlTXjx+3/8cqAnIFnELA/nkPAvngGAdxLdk2UzJ49255fj3tk/6FzerJBsKbM2CKz2azn21bT3v1ndOhwuFas+UvrF70hSTp1JlItOn6Zhf7Oq2mj8lq++i9J0vNtqmnztrAM53V5vpYWr9yv69dNkqQlP+/ThsVv6KMv1stodLG0Aw86nkHA/ngOAfviGURuREWJ7RjMZrPdBiEFBwdnaXngQ4cOZbvvgPIhdxsWssnXx12zvuwsby83JSQkq3qVYuo7ZL6Onbysbye9rG79v9fR45fUp3sDNXystJo9/8Vt+yta2E9zp72i6Gvx8vZyU/myhfVMp2nasfuk5RwnJ4P2/jpUz3WbriPHLlnafbzd1OjxMoqMvq5332ymE6evqNdbP2byLbCl8ENjeQbvI55BZIbn8P7iOcTNeAb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PjEajAgICtGbNGhtWifyseDE3Xb6SYusygEKLMQjYHuMQsC3GIJD/2HT1l5MnT2rjxo2aOnWqhg8fruHDhysyMlImk0kdO3bUu+++qw8++MCWJeIBvdKyitYtbacft3fXpDFh8iriLElq2+oJ7VzXSYd3va2Fn7ZWmdKeD/yYZf2LaN/WbvccD3m2lDZ+0V57t3RVlzeCrcdfbhGk/du66eUWQZKk0Npl5F/ywX8ekJ/l9hj8vXFmtLfT0H71tGNtJ323sbP69agle/s7n2YwBlHYMQ4B22IMorAxGAx58gUbByUtW7bUwIEDNWPGDF25ckU1a9ZUu3btFBISIk9PT126dEnffPONLUvEA6hXy1/vDKqvsZO+U8v2S+Xu5qjICc1UprSnIrqHqNegDWr66mKdu5CgD0c1fqDHLFPaU7Mmv6iilgtcNq+izvp0YnOt23xSr3VdoZZNA1W7RmlJUofXnlL/4ZvU4bWnJEk1gkvqwOFLuftkgcdQbo/BPxpnfcJD1KBeWXXrt1bh/dfppaaB6hN+Z8FtxiAKM8YhYFuMQQC5yaZBycsvv6zWrVurZcuWCggIUEZGhmJjY+/5wuOtdfMgfbUuSj/su6BLl5M17uMfVPOZUqr2RDEd+vmyjkVf06XLyVqx5rjKlinyQI/56aQWWrbq6D3HX2oWqCtXUxQ5+0edPZ+gyNk/6tVWT0iSing6a9+Biyri6awSxd0VdyU5V58n8LjK7TH4R+OsdYsgfTxjn2J+jdfxE9c09/NDatwgQBJjEIUb4xCwLcYgCie7PPqCTdcoqV+/vurWrSsvLy9bloGH5FXURdGnblhvm0x3di369Wy86oaU1hOBvjofm6g32j6lH/aef6DH7DFgncxm6f/6h+Y4XqWyr/Yc+F94duToZQ3uU0eSlHIrQ+XKFlFySrpefKGyFn/5y8M+NSBfyO0x+EfjzKuosy5d/t+bvqwss/XnMQZRmDEOAdtiDKIwYtebvGPTuGj06NEKDQ3VK6+8ookTJ2rPnj1KT0+3ZUn4G45GXVXD+uWUPZ3tlRer6MjRy4o6eV1fb4vR6s9f1087wvXMU8X14ZTvH+gxL1xMuu9xdzdHXYj9333JKekq5ucmSVq36YTWLm6nTdtj5Ohor1upGQ/3xIB8IrfH4B+Ns2NRV62fmtnZGdS6eaC+t7zhZAyiMGMcArbFGASQm2zaUbJ3715FR0frxx9/1IEDBzR06FAlJSWpRo0aCg0NVb169RQUFGTLEvEA5iw6qFrPltKqRa8rLS1Tz1QvoSGjtqj6k8XUqH55vdr5S50+E6/wTs9o9pQX1eatL//2z8rKMik9I8t6+3Z6lpyd7/xvPGvBQS1ZcVQN6pXVzYQ0rZjfVucuJGjAiM0P/RyBx1luj8E/Gmejx3+rGf9toepVi6msfxGVLOGuIf/eKokxiMKNcQjYFmMQhVOgrQsosGw+ASkoKEhvvvmmJk2apG+//VarV69W8+bNtWvXLrVu3VrPPfecrUvEn0hKTtcbb3+lvsO+VtTJa4r59YbWbjqpFk0qa/2WUzpy9LKSU9L130/2qkzpInoi0Pdv/6ybCbfl7fW/BV7dXB2UkWGy3k5OSVflit4KKFdU+w9eVIlibqoYwNQuFGy5PQb/aJxFnbyuhi8t1Nj/fq+k5HStXBuVowOMMYjCinEI2BZjEEBusmlHyd1iY2O1f/9+69fVq1cVGhqq0NDQP/9mPBauXE3RCw0raOTYHTKZzLKzM6io510XGDcHuTgbZWf39+fS/Xzsilo2rWy9/WSQX4596StV8NbJmBsqX7aoTsbckHdRZ+vWcEBBl1tj8M/GmclklouzUQHliqrHgHU5vpcxiMKOcQjYFmMQQG6waUfJF198oSFDhqhhw4YKCwvTggUL5OPjo//85z/au3evZs+erS5dutiyRPwFHV9/SqfP3NTWnb9Kkn48eElhDSuoc/tgvdiksqZPaK6r128p+uR1SXcuVEb7v/a/4PZvf9Wz1UuqXi1/Ge3tFN7pGX2355z1/hcaVtDm7aeVlHRbZUp7qkRxdyUm3c69Jwk8xnJrDP7ZOJOk/j1qae7nh3Tl2q0cxxmDKOwYh4BtMQYB5AabdpR8+umnCg0N1dChQ1WnTh3r7jdxcXE6c+aMKlSoIKPxsWl6wR/w9HBS947Pqnv/tdZjm7bHqGKAl95qHyw/X1edjLmhiCEblZl1p21x7eJ2GjvpO+uF7EHEJ6Rp7H+/08zJL+rWrQwlJd/WsNHbJEn29gYlJacrM8ukrTt/1YJPWuvshZs6efrGnzwqkP/l5hj8o3EmSSHPllKVQF/1+79NOb6PMYjCjnEI2BZjEEBuMZjNZrOtfvjly5c1ZswYmUwmRUZGSpImTJiguXPnyt7eXsWKFdP06dNVpUqVv/zYgSGRuV0uHiP+pTxUobyXfjx4idXEH0Mn9kcwBgsAxln+xjgsGBiH+RdjsGBgDOZvJ/ZH2LoE5FM2bdcYPny43Nzc1KdPH0nS6tWr9fnnn2v+/PkKCQnRxx9/rDFjxmjRokW2LBOPoQsXk353C2EAuYNxBtge4xCwLcYgUDjZNCg5dOiQNm7cqOLFiysrK0sff/yxunfvrlq1akmS2rVrp/nz59uyRAAAAAAAUIjYdDHX8uXLa/fu3ZKkmTNnKjExUZ07d7bef+DAAfn5+dmoOgAAAAAAUNjYtKNk1KhRioiI0KhRo2RnZ6fx48fL3d1d58+f14gRI3To0CF98MEHtiwRAAAAAAAUIjYNSp5++mlt27ZNMTExKlmypLy9vSVJTk5OatSokd555x0FBgbaskQAAAAAAFCI2HzvXWdnZ1WtWjXHsWLFiuWYggMAAAAAAPAo2HSNEgAAAAAAgMcJQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAIAFQQkAAAAAAICFwWw2m21dBAAAAAAAwOOAjhIAAAAAAAALghIAAAAAAAALghIAAAAAAAALghIAAAAAAAALghIAAAAAAAALghIAAAAAAAALghIAAAAAAAALghIAAAAAAAALghIAAAAAAAALghIAAAAAAAALghIAAIBHxGw227oEAADwJwhK8MhkZWXZugSg0PvtH2n80QY8GufPn9fu3btlMBgYdwAAPOYISvDI2NvbS7rzZlEiOAEetczMTBkMBklSenq6JMlgMMhkMtmyLKDAM5vN2r59uyIiIvTdd98RlgA29HvvPxmTAO5mMPNbAY/QypUrNXbsWP3www9ydHS0dTlAoWE2m62hyNtvvy0nJycVL15co0aNkiSZTCbZ2ZGdA3klKSlJS5cu1ZIlS/Tuu++qQYMG1nEJ4NHIvtaZTCYtXLhQZrNZQUFBCgkJkdFoZEwCsCIoQZ7KysqydpJIdz7RjoiIUL169dSpUycuRsAjcHcIMm7cOP3yyy8KCQnR999/Lz8/P02bNu2e8wDkvuTkZC1evFhLly4lLAFsxGw2q02bNnJzc1NGRoaKFi0qNzc3jRs3jrAEgBXviJGnfjvdxmAwqFatWjp8+LD1IkRWB+St7PBjwYIFOnfunAYNGqS+fftqzJgxSkhIUJ8+faznMQ0HyF13X+Pc3d31xhtvqF27dnr33Xf17bffMg0HeMR+/vlnOTo6auHChVq6dKlu3Lihq1ev6sqVK8rKyiIkASCJoASPwMqVK9WiRQt99tlnunz5sjp27KijR49q3rx5ksQFCchD2X+A7d27V7t27dKPP/6oxMREGQwGBQQE6F//+pdSUlLUuXNnSaKjBMgF58+f18aNGyXpniCEsAR4tH77AUB6erqOHz+us2fP6sMPP1RCQoJGjx6tWbNmaeXKlTaqEsDjhnfEyHW/XSSrUaNGev/99/X111/r3//+t+bOnasBAwbo4MGDunbtmo2qBAq27HGYHUTWrl1bPXv2VEBAgObOnavz58/LaDQqMDBQAwcOlLOzs+Li4mxZMlBg7N+/XyNGjNDatWsl/XFYMmbMGG3bto0PDYA8kD2l1Gw2KzExUZIUEBCgevXqqVevXtq+fbsWLlyogIAARUVFqVixYjauGMDjgjVKkKvuXpNk9+7dun37tqpXry5vb29duHBBp06d0uTJk5WQkKDr169r+vTpeu6555gPCuSiuxer+/TTT5WRkSFXV1d16dJFR44c0cKFC+Xp6amePXuqZMmSysrKUlZWFgssA7nk1q1bWrt2rWbMmKH+/furVatWknTPtS45OVlz5szRtm3btHTpUrm4uHAtBHLJ3eOtc+fOql27tnr06CE7Ozt98cUXWrBggerWrat//OMfioqK0ty5c7Vs2TKVKVPGxpUDeBwQlCBP9O3bVydPnpSrq6saN26siIiIHPevXr1a69evV2xsrJYsWSJPT08bVQoUTGazWW3btlWRIkXk4+Ojc+fO6dq1a1q8eLHOnz+vJUuWSJIGDx6sEiVK2LhaoOBJTU3VqlWrNGvWrD8NSzIyMuTl5WWrUoEC7dKlSxo9erQ6d+6smjVrymg0SrrzXvTYsWP65Zdf5OHhoX79+unJJ5+0cbUAHhdGWxeAgmfTpk06ffq0Fi1aJDs7O7m7uysxMVFXrlxRpUqVJEmtWrVSrVq1NHbsWMXHxxOUAA/pt398nThxQs7Ozpo5c6a1y6t3797q0aOHvvrqK924cUO7du3KsSsVgNzj4uKi1q1bS5KmTJki6c61L3saTvZ4dXd3t1WJQIE3aNAgJSQkKCsrS0899ZSMRqMyMzNlNBrVqlUrtWrVSqmpqbKzs5OTk5OtywXwGGGNEuS6lJQU+fn5ydfXV0WLFpWjo6M2b96szp07KyUlxXreunXrtHPnTjk7O9uwWiB/O3funGJiYu5p1799+7aOHj2q6Oho67FRo0YpIyND0dHRCgsL09ChQ+Xn5/eoSwYKpLsXjMz+d3ZYEh4erilTpmj16tWS7l2zBEDe6Ny5s65cuaKff/5ZUVFRMpvNMhqNOcari4sLIQmAexCU4KH8duFWSSpVqpSio6O1f/9+6w4aderUkb+/v5KTk63nhYaG6quvvlLx4sUfWb1AQXL79m0tWLBAhw4dsh4zm80ym80qX7686tevr++++866aLK7u7scHR2VlpZmvQ3g4WVmZlqvd6mpqbp165b1vrvDksjISC1fvlwSO74BuS0zMzPH7fT0dD311FP66KOP5Ofnp61btyo+Pl4SO7wB+HNMvcHfdvfCrVu2bJGLi4sqVKigOnXqqGnTpoqMjFT37t1Vu3ZtHThwwHpxku78Mcc8UODhODk5qUePHvLz85PZbFZsbKz8/f0lSZ6engoJCdHWrVt16dIlBQUF6erVq0pISGBNEiAX3f0Jdbdu3eTs7CxXV1d16tRJwcHBkv4Xlty+fVsLFy5Us2bN5ObmRlgC5BKTyWQdhxMmTLBOp2nXrp0CAwP10UcfaeDAgZKkbt26ydfX18YVA3jcsZgrHlrv3r119uxZlShRQjdv3tT06dMlSfPmzdOyZcv0xBNP6Pz58/rXv/6lZs2a2bhaoGCaN2+e1qxZowkTJljXApKk9evX6/Dhwzp48KBKliypXr166YknnrBhpUDB1LVrV7m4uKhFixZasGCB7OzsNHDgQNWsWdN6TlpamtLT01mXC8gDZrNZb7zxhjw9PVWpUiXFxcVp06ZNmjFjhkJDQ3X06FF169ZNr7/+uvr3709XCYA/RFCCh7J161ZNmDBBS5cu1c6dO/XJJ5/IxcVFU6dOVZkyZXTixAmZzWY5OjoqICCAbYCBPHLkyBGtXr1aZ86c0fDhw3OEJdKdFmSDwSAHBwcbVQgUXMnJyXrzzTc1ceJEFStWTMOHD5ckJSQkaPjw4apataqNKwQKvtjYWA0bNkzTp0+3hpGTJ0/W4sWLtWrVKpUqVcq60HnZsmVtXC2Axx1RKh5KXFycihYtKi8vL0VFRalOnTqqVq2aBg0apKioKAUGBiooKEgBAQGSmJMN5Ia78+3sBemqV6+utm3bqmzZsho7dqxOnTqV435HR0dCEiCX3L0QpCQ5ODjIw8NDHh4e+uCDD+Tk5KS+ffvq6tWr6tGjhzZv3myjSoGC67ef9ZrNZkVFRenAgQPWY926dZO/v79Onz4tSQoMDCQkAfBACErwwO5+Y5iamipJatiwofr27astW7bo66+/VkREhIKDg3XkyBG1a9dON27csFW5QIGUmZmZI3C8e/G6KlWq6LXXXlO5cuU0btw4RUVF0VoM5LK7F25NTk5WbGysnJycNHfuXCUnJ+unn37SpEmTVKVKFZUtW1YtW7ZUxYoVbVw1ULD89lqYmpoqf39/hYWFad++fYqJiZEkeXh4yMnJ6b6bDwDAH2HqDR7I3VNmPvzwQ1WtWlVNmjSRo6OjJGnixIm6deuWRo4cqc8++0ypqalq3LixAgMDbVk2UKCYTCbZ2dnJZDJp4MCBSktLU+3atdWpUydJsi6uHBUVpXnz5iklJUWTJk2Sg4MD3VxALsi+FppMJnXv3l23bt2Ss7OzRo4cqYoVK+rKlSvq1q2bmjRpIoPBoK1bt2rOnDny9va2delAgXH3tXDYsGFKTk5WuXLlNHDgQH377bdauHChfH19VaxYMRmNRq1atUrLli1TqVKlbF06gHyEXW/wp+4OSc6ePatjx46pdevW1pBEknW6zbVr17Rjxw5NnTrVGpKwLgmQO+zs7GQ2m/X666/L09NTDRs2VPPmzWVvb6+MjAxrUFKlShV169ZNXl5eOcYpgIeTfS3r37+/HB0d1aNHD9nb26tixYqKj49XsWLF9OKLL2rnzp26ceOGJk2aREgC5LLsjq6OHTvKw8NDtWrVUpkyZeTo6Kjnn39e5cuX186dO/XDDz/I399fs2bNIiQB8JfRUYIHtnz5ckVHR+vgwYOaP3++3N3drfclJiZq165dOnjwoBo0aKAGDRoQkAB54OzZsxoxYoSmTJkiHx8fzZo1SxcuXFB6err69Omj0qVL27pEoEBLT09XRESEunfvrtq1a8tkMikjI0MdO3ZUeHi4wsLCdPv2baWmpqpo0aK2LhcokOLi4jRw4EBNnTpVPj4+kqQbN25o5MiRGjJkiMqXLy+z2Syz2cwUVAB/C7858Lvuns+ZkZGh6OhoRUdHKzU11RqSZK9b4unpqRYtWuidd96xhiQA/r5Tp05p3bp19xx3c3PTkSNHNHjwYEVERGjNmjUqW7asoqOjtXHjRhtUChRsv1241dHRUdevX9fWrVsl3fl028nJSZUrV9ahQ4ckSU5OToQkQC767Ti0s7PTmTNntHv3buuxrKwsxcfH68iRI5LudIARkgD4u/jtgd+V3cb/zTffyMHBQUOGDFH9+vUlScuWLVN6erp1juhvGQwGukmAv8lsNuvAgQOKi4vLcTwzM1O+vr5avny5qlWrpnr16mnt2rXq1q2bSpQoobS0NBtVDBRMv124NXuB8g4dOujXX3/VypUrrefe71oI4OHdPQ6zsrKUlJSkYsWKKSwsTAcOHFBUVJQkyc/PT25ubsrIyLBluQAKCKbe4A/FxMSoRYsW6t+/v3r16qX09HRNnz5dp0+fVoMGDfTSSy+xBgKQBzIyMuTg4CCTyaQffvhBzz333D3Ho6KitGfPHsXHx2vJkiVaunSpKlWqZOPKgYIhMzNTRqNRWVlZCg8PV2JiolxcXNSkSRO1b99eH330kY4dO6bExERVqVJF27Zt0+LFixmDQC66e+HWXr16KSEhQbVr19aAAQO0e/duzZw5U0WKFJGnp6c8PDy0YsUKffHFF2wBDOChsZgrcsjKyrJ2kkhSxYoVNW/ePIWHh0uSevXqpZ49e2rmzJnavHmzTCaT2rZtS/cIkMscHBwkSdu3b9eAAQM0duxYtWzZ0hqSSHfWBlqzZo0qVqyoRYsW8Qca8JCSkpKUkZEhR0dH6xTTd999V2azWaNGjdKvv/6qYcOGqUSJEurVq5cuXryotWvXqkyZMurevTvbAAO5LLuTpFOnTnJ1dVWXLl1Uq1YtSVLdunXl7++vXbt26dtvv5Wjo6Pmz59PSAIgVxCUIIfskGTt2rVq2bKlpDsXopkzZ6p79+6yt7fX22+/rbffflvTp09X1apVCUmAPFSvXj2NGDFCkydPlslkUqtWraxvHOvUqaMvv/xSZrPZGqwA+Huio6M1fPhwSdL169c1ZswY1a9fX0lJSWrevLmqV6+uZcuWqXLlyipRooS2b9+u1q1bq0qVKjauHCjYrly5IoPBoMGDByswMFBTpkxRTEyM0tPT1bNnT73xxht64403rN0nAJAbCEpwj9OnT2vcuHE6fPiw3nnnHUl3/lgbOXKk3nvvPdnZ2al79+4aMGAAIQmQi+5+k5f9b1dXV7Vq1Upms1lTpkyRJLVq1UrSnQ4wo5Ff48DDioqKUvv27dW+fXuFhoZq9+7d6tevn+bOnasiRYpozZo1On78uH766SdNnz5dMTExmjt3rlq0aEFICeSBu6+HXl5eunbtmnr37q2goCDFxsaqS5cuWrlypbZs2aKnn35akghJAOQqfqMgx+42klShQgVNnDhR+/fv13vvvWc9XrlyZZUsWVIfffSRzp49+6jLBAq0uxerS09P182bN633ubi4qHXr1goPD1dkZKSWL18uSTmmyQH4e+Lj4xUeHq5atWpp6NChCg0N1eDBg9WoUSNNnDhRzZs3V3x8vFavXq1PPvlEAQEB+umnn+Tv788fZkAeuDsk2bFjhxISErRixQp16NBBzZo106pVq9SqVSv5+voqJSWFnRYB5AkWcy3k7r4YLV26VLdu3VLZsmX1/PPPa+/evRo7dqxq1qypkSNH6vDhwzp8+LCaNWsmPz8/G1cOFBxms1kGg0Emk0k9e/ZUamqqXFxcNGrUKPn7+1vPS01N1bJly7Ry5UotXrxYbm5udHUBDykpKUnTpk3T/v371bt3bz3//POSpOXLl2vHjh3673//q40bN2rjxo26cOGCnn32WW3atEnz589n2g2Qy+5+Xzpz5kzNmDFDS5YsUWBgoKQ73V9ffPGF7O3ttXLlyhz3AUBuIiiBJKlfv346efKkgoKCVKpUKQ0ZMkQmk0k//vijhgwZouLFi+vixYt69913FRYWJul/f9wByB09evSQwWDQa6+9JhcXF9WtW1fJycnWRSUlKS0tTenp6fL09LRhpUDBkpiYqDlz5mj79u0aNWqUatSoobCwMMXHx6tPnz4KDQ2Vj4+Pdu3aJW9vb5UvX17lypWzddlAgXJ3SDJr1izNnz9fEyZMUN26da3nnD59Wh988IHKlSuntm3bKigoyFblAijgCEqg6OhoDRs2TLNmzZKXl5eMRqMSExO1ZcsWtWnTRleuXNHOnTsVGBio4OBgAhIgD6Slpal3794aOHCgqlWrJpPJpLS0NL311lvq27evGjRoYOsSgQItOyzZvHmz4uLi1Lx5cwUFBWnp0qVyd3dXfHy8+vXrZ13oHEDuyN6KO9vs2bM1d+5cTZo0SXXq1Lnv97BwK4C8xm8YKCkpSTdu3JCrq6v1QpWQkKCRI0dqz549KlasmNq2bavg4GBJIiQBckH2Fr/Z7OzsFBsbq+3bt1tvu7q6yt/fX0eOHLFFiUCh4unpqW7duqlJkyZydXVVs2bN1KlTJ61du1Zjx47Va6+9pieffNLWZQIFQlxcnEaOHClJMhqN1vXyVq5cqVmzZv1uSJL9+S4hCYC8xm+ZQua3C7dK0jPPPCNvb2/NmjXLeqx06dKqW7eunJycHmV5QKHw24VbExMT5ejoqDfffFPHjh3T119/bT2XN4PAo+Pp6amuXbvq1Vdf1bhx47R582bZ29urUqVKCg8PV8WKFW1dIlAgODk5afny5dbdFbMXJ69Ro4Zmz579u50kfFgH4FFhX8lCxGQyWS9En332mW7duiUvLy+1b99eb775ptatW6f3339fbdu21dGjR3Xs2DG5uLjYuGqgYDGbzTIajdaFW1NSUuTs7Kw2bdqobdu2On36tD7//HN9/vnnCggI0HfffafevXvbumyg0MjuLLG3t9eYMWPk5OSkf/zjH7YuCygQEhMTZW9vr/T0dFWuXFk7duxQz5499emnn0oSa/8AeGwQlBQi2Z9M9+vXT6dOndLTTz+tlJQUSVJYWJjc3Nw0Z84c7d27V3Z2dho1ahQr+gO5LPvTsGHDhikrK0sRERE6ffq0Bg4cqPnz5ysiIkJnz57VunXrVK5cOS1evJhPsYFHzNPTU2+99ZYcHBxUoUIFW5cDFAi//PKL+vTpo08//VQGg0Hu7u6aPHmyevfunSMsycrKsn6wBwC2wmKuBdhvF7oymUw6d+6cBg4cqOnTp6t48eIyGAxKTEzUmjVr1KFDB0nSjRs3ZGdnp6JFi7JwK5AHzGaz+vbtqxYtWqhZs2YaMWKEDh06pPHjxysuLk6NGze2dYkAxIKRQG45fvy43njjDXXo0EGDBg2SJP3444+qWbOmLl26pI4dO6pSpUqEJQAeG1z9C6iMjAy99tprmjNnjmJiYiTd6ShJTEzUxYsXZW9vL4PBILPZrMzMTI0fP15btmyRJHl7e6to0aKSmAsK5Ibfrg1kMBiUkpKijRs3auzYsTpw4ICmTZumU6dOKTIy8r5rCQF49AhJgIcXFRWl9u3bq2vXrho0aJB1MfOaNWtKkkqWLKlFixYpJiZGPXv2lHRnzRKuhQBsiXcABVRmZqa8vLwUGRmpSZMmWRP66tWr68knn1RkZKSkO3+weXt7q169enJ3d7dlyUCBZW9vL5PJpPnz5ys2NlaSFB4erqioKK1cuVJz585VQECAjh8/roCAAP44AwAUCPHx8QoPD1ft2rXVt29fSXcCyO3bt+vatWvW80qUKKGFCxfqzJkz1g5nOkoA2BLvxgsoFxcXvfrqq/Lx8VFwcLDWr1+vDh06aNeuXXrhhReUkJCgQYMG6eDBg1q+fLkOHjwoDw8PW5cNFCgZGRnWfy9btkzff/+9XF1dJd0JLd966y1Vq1ZNgwcP1ujRo/XVV18pPDycTi4AQIFgNBrVvHlzXb16VVu3bpUkzZw5U3379tXNmzdznFuiRAnNmTNHKSkpunTpkg2qBYD/YY2SAi77QjRnzhy9//77Onz4sEqVKqXQ0FDt2bNHFy9elNFoVOfOndWsWTNblwvkezdu3FBCQoJcXV1VvHhxSdLatWu1Z88e+fj46J///KcMBoMMBoNSU1OtawSVLFlSVatWVUBAgI2fAQAAuScxMVFz5szRzp07VbFiRf30008aO3as6tate9/zMzMzZTSy3wQA2yIoKaCyF6C7evWqevXqpZ49e+r06dOaOXOmnnjiCUVFRSkiIkJPPvmkqlevLmdnZxZuBR5SVFSU+vbtKx8fH8XExCgiIkIuLi76+uuvFR8frzfffFNt27aVyWSyhiUAABR0iYmJmjt3rubPn6+uXbtap+Hw3hPA44qpNwVU9hoHRYoU0f/7f/9P7733nhYtWqSpU6dqwYIF6tSpk1asWCF3d3c5OztLYuFW4GFkL1bXvHlzRUZGasiQIfr666/l4eGhTp06SZI2bdqk2NhY2dnZMd4AAIWGp6enunbtqk6dOmnLli3WaTjZGwsAwOOGjpJCIC4uTh07dlRwcLA++ugj6/Fr167J19fXhpUBBUNycrJatmwpf39/LVy40Hp88uTJ2rx5s9avX69NmzZp/fr1CgwM1KuvvqqSJUvasGIAAB697Gk427dv1z//+U81btzY1iUBwH3RUVIIlChRQkOHDtWOHTu0c+dO63EfHx8bVgUUHI6OjurYsaNOnjypFStWWI/XqlVLrq6uunXrlpo2barGjRvr5MmTWrBggS5fvmzDigEAePQ8PT3VrVs3hYWFafTo0TnelwLA44SVkgqJBg0aqHbt2lq9erVCQkLk6upK6z+QSxwdHdWpUycZjUZ98MEHKlKkiBo1aqTBgwfr1VdflZubmySpdevWSk9P1/79++Xg4GDjqgEAePQ8PT311ltvycHBQRUqVLB1OQBwX0y9KUSio6OVlJSkmjVr2roUoEDKyMjQkiVL9PHHH+v27dvq2rWrBgwYICnnKv7Jyclyd3e3ZakAANhU9sYDAPA4oqOkEAkKCrJ1CUCB5uDgoPbt28vR0VHjx49XuXLlJN1Z1d/e3t66uj8hCQCgsCMkAfA4IygBgFzk4OCgNm3aKD09XWPHjpXBYNDLL79s67IAAAAAPCCCEgDIZdmdJfb29ho+fLiMRqNatmxp67IAAAAAPACCEgDIAw4ODnrttddkNBpVtWpVW5cDAAAA4AGxmCsAAAAAAIAFqygBAAAAAABYEJQAAAAAAABYEJQAAAAAAABYEJQAAAAAAABYEJQAAAAAAABYEJQAAAAAAABYEJQAAJBHPv30U+3atct6OzY2VqdPn9b58+d14cKFHF/nzp3TqVOnlJSUlOMx9u/fr7Vr1yo9PT3H8c8//1xbtmz50xo2bdqkTz75xHo7KioqR00PYujQoTl+VlpamrKysu45z2Qy3VMnAABAfmO0dQEAABRU8fHxioiI0Lx581SjRg29//77+uabb2Rvby9JyszMlJ2dnezs7GQ2m5WZmakpU6aoadOm1sdYunSpdu7cqXr16snHx8d6fPny5XrqqacUFhb2hzVERUVp37596tWrlyRp8+bN2rJli+rXr28958aNG9qwYYPat29vre1ux48fV40aNay3g4ODf/fnVa1aVStXrvyTVwYAAODxRVACAEAeGT58uOLj4zV06FBt2rRJ06ZNk53d/5o5X3nlFTVs2FB9+/aVJJnNZpnNZuv9t27d0o4dO/Tmm2/mCEkkyd3dXe7u7n9ag4ODQ46faTQalZmZqSNHjujnn3/W7t27tXPnTvn4+Kh06dJq2LDhfR/DwcHBenvRokUqWrSoXFxcrMcyMzPv6YYBAADIjwhKAADIQ++9954uXrwoo9Go3bt3Ky4uTi+//PI95505c0Yff/yxevTooaCgIEl3uklu3bqltm3b6vz583J0dLSGHpmZmUpNTdXVq1cl/W/aS7FixeTk5KT09HQZDAbr4989Jebs2bMaPXq0goOD1aRJEw0fPlylS5fOUU9CQoJOnDghBwcHpaWl6cKFCzpw4IB8fX0VEhKS668TAADA48JgvvujKwAA8NAyMjJkZ2d3zzSWZcuWafz48dq+fbuKFCmSo6Nk2rRpmj17trZu3SpfX1+lpaUpLCxMTk5OWrJkiZ577rkH+tnLli3T008/rf/85z/6/PPPc9zXtWtXeXh4aMOGDVq3bt0937tz506VLVtWAQEB+uGHH9SlS5d7zunUqZNGjBjxF14NAACA/IWOEgAActmXX36pd99913p71qxZatCggV555RVNmTJFCxcuVJ8+faz3Z2Zmavny5Wrbtq18fX0lSbNnz9aVK1dUtmxZ+fj4aO/evXJycrJ2lHTt2lVVq1bVoEGDJN3pKMnIyLBOh+nfv78iIiK0YMEC7du3T1OnTpWjo6MWLVqkW7duKSsrK0eQk5GRoenTp8vZ2Vnz58/XU089pQ0bNujMmTPq3bu3hg8frueff17Xr19XdHS0jMb7v4XIzMyUm5ub/P39c/U1BQAAeFQISgAAyGVNmjRRjRo1ZG9vr+bNm1vX93BwcFCLFi104sSJHOfv27dP169fV9euXSVJMTExmjlzpqpXr66bN2/Kzs5ORYsWzfE92R0rTk5O1mN3rxlSpEgRSZKTk5OMRqM1gHnyySd18eJFhYSE5Dg/KSlJWVlZmj17tiTJw8NDHh4e1h1y3N3d5ezsrCVLlmj9+vVydHSUwWBQamqq7OzsrHXcvn1br7/+ut55552Hfh0BAABsgaAEAIBc5u3tLW9vb+ttBwcHZWVlKTU1VQMHDswRUEhSvXr19P3338vd3V0pKSmKjIxUtWrV9Morr2jGjBkPXc/Nmzc1btw4ValSRa1atdI333yjmzdv5jjHYDCoePHi8vLyynF8w4YNku5sdbxq1SrNmzdPH374ofX+3r17q1y5cho2bNhD1wkAAPA4ICgBAOAROHbsmF599dV7jh89elTTpk3LcWzNmjXy8PDQnj17rMdSU1P19NNP5zhv3759mjt3riTJx8dHP/zwg/W+xMREbd26VZs2bVJMTIzKlSunV155RZMmTfrd8KV69epavny59Xb2zjheXl5q3bq1Zs6cqa1bt6p27dqSlCMMku5sRVylSpUHeDUAAAAeXwQlAAA8AoGBgdqyZYscHR2ta4N0795d9erVs065MZlMun37tsqUKZNjxxpJ1u+ZNGmSgoODc9y3adMmffbZZ9bbaWlpatSokdLS0uTv768aNWpYwxhHR0c9++yz94Qlc+bM0YEDB6y3TSaTJkyYoLCwMF24cEGlSpVSly5drOucLFq0SDt27LCev3LlSo0aNUpffvklYQkAAMjX7GxdAAAAhcFnn32mxMRElShRQn5+fvLz85O9vb1cXV2tt4sXL66yZcveE5JIsq5z4uvrK39//xxfXl5e1vslydnZWZ07d9aqVav00ksv5XgcOzs7GY1GeXp65vhycnLK8XOnT5+uo0ePWheLlaQBAwaoUaNG2rBhg9q0aSNXV1frfS+++KLKly+v4cOHKysrK9deNwAAgEeNjhIAAPLYqlWrtGLFCpUqVUrVqlX7W49hMBisO97cz2+3Is7eVWfz5s33nLtv3z4FBQXdc7xWrVrWfzdr1kxBQUEqV65cjnO2bdumCxcu6K233spx3NHRUaNGjVLHjh21YMGC+24tDAAAkB8QlAAAkEeuXLki6c52we+9955atmz5l77fZDLJbDbnuH358mWdPXs2x3nXr1//S10ctWrV0sKFC3Mcmz59unbv3m29XbFiRVWsWDHHORkZGRo/frxeeukllShRQpJy1FerVi2Fhobq2rVrD1wLAADA44agBACAPLJkyRJJ0r///W+1bdv2L39/ZmamTCaTpDshhSQNGTLkvucWL148x+0LFy7o1KlTOnjwYI4thKXf7ygJCQm572NnZGQoIyNDDg4O+vjjj+Xl5aXdu3dr9+7d+umnn3KsmTJnzpz7Th0CAADILwhKAADII926dZOvr6/at29/3/szMjKsQcj9JCYmKj09XZKsHSMLFiyw7jqTbeXKlfroo49yHEtNTdWAAQNUpkyZHOuMmEym313M9e5dc+6Wnp5uDWqyF2qNjY3Vtm3b1LRp0xzPj5AEAADkdwbz3T2zAADgkWnSpIkaN26soUOH/um5ZrNZsbGx8vPzu6dD5K+YOHGiDh06dM/UGwAAANxBUAIAAAAAAGDB9sAAAAAAAAAWBCUAAAAAAAAWBCUAAAAAAAAWBCUAAAAAAAAWBCUAAAAAAAAWBCUAAAAAAAAWBCUAAAAAAAAWBCUAAAAAAAAWBCUAAAAAAAAW/x8k4esObHRpgQAAAABJRU5ErkJggg=="
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 10
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "# 分组柱状图",
   "id": "35232eb608d3512a"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-06-12T13:15:49.933434Z",
     "start_time": "2025-06-12T13:15:49.749374Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# 设置柱状图参数\n",
    "bar_width = 0.15  # 调整宽度适应更多模型\n",
    "colors = ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', '#9467bd']  # 新增紫色给SVM\n",
    "\n",
    "# 计算柱子位置\n",
    "positions = np.arange(len(metrics))\n",
    "model_offsets = [positions + i*bar_width for i in range(len(models))]\n",
    "\n",
    "plt.figure(figsize=(14, 8))\n",
    "for i, model in enumerate(models):\n",
    "    plt.bar(model_offsets[i], \n",
    "            df.loc[model], \n",
    "            width=bar_width, \n",
    "            color=colors[i],\n",
    "            edgecolor='grey',\n",
    "            label=model)\n",
    "\n",
    "# 优化标签显示\n",
    "plt.xticks(positions + bar_width*2, metrics, rotation=25)\n",
    "plt.xlabel('评估指标', fontsize=12, labelpad=10)\n",
    "plt.ylabel('得分', fontsize=12)\n",
    "plt.title('模型性能对比', fontsize=14, pad=20)\n",
    "plt.ylim(0.8, 1.0)\n",
    "\n",
    "# 调整图例位置\n",
    "plt.legend(loc='upper left', bbox_to_anchor=(1, 1), frameon=False)\n",
    "plt.grid(axis='y', alpha=0.3)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ],
   "id": "a508e7d195c069ac",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1400x800 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 11
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "# 时间热度图",
   "id": "45a57f63480749c0"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-06-12T13:15:50.180233Z",
     "start_time": "2025-06-12T13:15:49.952374Z"
    }
   },
   "cell_type": "code",
   "source": [
    "from matplotlib.colors import LogNorm\n",
    "\n",
    "# 更新训练时间数据（添加SVM）\n",
    "training_times = [9.4683, 22.1014, 256.8687, 387.9466, 162.9384]  # SVM时间\n",
    "df_time = pd.DataFrame([training_times],\n",
    "                       columns=models,\n",
    "                       index=['Training Time']).T\n",
    "\n",
    "# 调整对数范围\n",
    "log_norm = LogNorm(vmin=1, vmax=400)  # 扩展上限\n",
    "\n",
    "plt.figure(figsize=(13, 6))\n",
    "ax = sns.heatmap(\n",
    "    df_time,\n",
    "    annot=True,\n",
    "    fmt=\".1f\",  # 改为显示1位小数\n",
    "    cmap=\"YlOrRd_r\",\n",
    "    norm=log_norm,\n",
    "    linewidths=0.5,\n",
    "    annot_kws={'size': 12, 'weight': 'bold'},\n",
    "    cbar_kws={\n",
    "        'label': '训练时间（秒） - 对数刻度',\n",
    "        'ticks': [1, 10, 100, 400]\n",
    "    }\n",
    ")\n",
    "\n",
    "ax.set_title('模型训练时间对比\\n', \n",
    "            fontsize=16, \n",
    "            fontweight='bold',\n",
    "            pad=20)\n",
    "plt.xlabel('')\n",
    "plt.ylabel('机器学习模型', fontsize=12)\n",
    "cbar = ax.collections[0].colorbar\n",
    "cbar.set_ticklabels(['1秒', '10秒', '100秒', '400秒'])  # 更新标签\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ],
   "id": "f65d18b805ffafff",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1300x600 with 2 Axes>"
      ],
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 12
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
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   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
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 },
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 "nbformat_minor": 5
}
